From c2f104d8823d23a47510ac46415d3714392a5aa4 Mon Sep 17 00:00:00 2001 From: Shreya Verma <147494302+vermu490@users.noreply.github.com> Date: Wed, 30 Oct 2024 23:14:51 +0530 Subject: [PATCH 1/2] Add Social Network Analysis Project to Unsupervised Learning --- .../Social Network Analysis/README.md | 145 ++++ .../Social Network Analysis.ipynb | 651 ++++++++++++++++++ .../data/star-wars-network-edges.csv | 60 ++ .../data/star-wars-network-nodes.csv | 23 + .../img/hastie_etal-f12-1.png | Bin 0 -> 18991 bytes .../img/net-1-edge.png | Bin 0 -> 20344 bytes .../img/net-1-node.png | Bin 0 -> 19596 bytes .../Social Network Analysis/img/net-1.png | Bin 0 -> 17028 bytes .../img/precision-recall.png | Bin 0 -> 21410 bytes .../img/supervised-learning.png | Bin 0 -> 89872 bytes 10 files changed, 879 insertions(+) create mode 100644 Unsupervised Learning/Social Network Analysis/README.md create mode 100644 Unsupervised Learning/Social Network Analysis/Social Network Analysis.ipynb create mode 100644 Unsupervised Learning/Social Network Analysis/data/star-wars-network-edges.csv create mode 100644 Unsupervised Learning/Social Network Analysis/data/star-wars-network-nodes.csv create mode 100644 Unsupervised Learning/Social Network Analysis/img/hastie_etal-f12-1.png create mode 100644 Unsupervised Learning/Social Network Analysis/img/net-1-edge.png create mode 100644 Unsupervised Learning/Social Network Analysis/img/net-1-node.png create mode 100644 Unsupervised Learning/Social Network Analysis/img/net-1.png create mode 100644 Unsupervised Learning/Social Network Analysis/img/precision-recall.png create mode 100644 Unsupervised Learning/Social Network Analysis/img/supervised-learning.png diff --git a/Unsupervised Learning/Social Network Analysis/README.md b/Unsupervised Learning/Social Network Analysis/README.md new file mode 100644 index 00000000..d399c3ca --- /dev/null +++ b/Unsupervised Learning/Social Network Analysis/README.md @@ -0,0 +1,145 @@ +```markdown +# Social Network Analysis of Star Wars Episode IV + +This project utilizes Social Network Analysis (SNA) to explore and visualize the interactions between characters in *Star Wars Episode IV*. The analysis is performed using the `networkx` library for network creation and analysis, and `matplotlib` for visualization. + +## Table of Contents +- [Introduction](#introduction) +- [Requirements](#requirements) +- [Data](#data) +- [Code Overview](#code-overview) +- [Visualizations](#visualizations) +- [Network Statistics](#network-statistics) +- [Traditional Methods vs. Our Model](#traditional-methods-vs-our-model) +- [How to Run the Code](#how-to-run-the-code) +- [License](#license) + +## Introduction +Social Network Analysis (SNA) focuses on the relationships between entities rather than the entities themselves. In this project, we analyze the co-occurrences of characters in *Star Wars Episode IV* using graph theory to uncover patterns in their interactions. + +## Requirements +To run this project, you will need: +- Python 3.x +- `networkx` +- `matplotlib` +- `pandas` (optional, if you need to manipulate the data) + +You can install the required libraries using pip: +```bash +pip install networkx matplotlib pandas +``` + +## Data +The network data is provided in a CSV file named `star-wars-network-edges.csv`, which contains edges representing interactions between characters. The file format is as follows: +``` +node1,node2,weight +``` +- `node1`: Character 1 +- `node2`: Character 2 +- `weight`: Number of scenes in which both characters appeared together + +## Code Overview +The code is organized into several sections: + +1. **Importing Libraries** + ```python + import networkx as nx + import matplotlib + import matplotlib.pyplot as plt + %matplotlib inline + ``` + +2. **Reading the Weighted Edgelist** + ```python + G = nx.read_weighted_edgelist('data/star-wars-network-edges.csv', delimiter=",") + ``` + +3. **Viewing Edges and Nodes** + ```python + G.edges() + G.nodes() + ``` + +4. **Getting Edge Attributes** + ```python + nx.get_edge_attributes(G, 'weight') + ``` + +5. **Drawing the Basic Graph** + ```python + nx.draw(G) + ``` + +6. **Visualizing with Different Layouts** + - **Fruchterman-Reingold Layout:** + ```python + pos = nx.fruchterman_reingold_layout(G) + nx.draw_networkx_labels(G, pos) + nx.draw(G, pos) + ``` + - **Circular Layout:** + ```python + pos = nx.circular_layout(G) + nx.draw_networkx_labels(G, pos) + nx.draw(G, pos) + ``` + +7. **Visualizing Edges with Varying Widths Based on Weights** + ```python + esmall = [(u, v) for (u, v, d) in G.edges(data=True) if d['weight'] < 5] + emid = [(u, v) for (u, v, d) in G.edges(data=True) if d['weight'] >= 5 and d['weight'] < 10] + elarge = [(u, v) for (u, v, d) in G.edges(data=True) if d['weight'] >= 10] + + nx.draw_networkx_edges(G, pos, edgelist=elarge, width=4, alpha=0.5) + nx.draw_networkx_edges(G, pos, edgelist=emid, width=2, alpha=0.5) + nx.draw_networkx_edges(G, pos, edgelist=esmall, width=1, alpha=0.5) + ``` + +8. **Coloring Nodes Based on Character Alignment** + ```python + dark_side = ["DARTH VADER", "MOTTI", "TARKIN"] + light_side = ["R2-D2", "CHEWBACCA", "C-3PO", "LUKE", "CAMIE", "BIGGS", + "LEIA", "BERU", "OWEN", "OBI-WAN", "HAN", "DODONNA", + "GOLD LEADER", "WEDGE", "RED LEADER", "RED TEN"] + other = ["GREEDO", "JABBA"] + + nx.draw_networkx_nodes(G, pos, node_color='red', nodelist=dark_side) + nx.draw_networkx_nodes(G, pos, node_color='yellow', nodelist=light_side) + nx.draw_networkx_nodes(G, pos, node_color='gray', nodelist=other) + ``` + +## Visualizations +The visualizations created in this project illustrate the relationships among characters based on their co-occurrences in scenes. Different layouts help in understanding the structure and clustering of characters. + +## Network Statistics +The project also computes various network statistics, including: +- **Density**: Measures how many of the possible connections in the network have been made. +- **Degree**: Number of edges connected to each node. + ```python + nx.density(G) + nx.degree(G) + ``` + +## Traditional Methods vs. Our Model +With the massive amount of information generated by social networks every day, organizing this data is crucial. Traditional methods often involve hierarchical clustering, which does not allow the formation of overlapping clusters and requires prior knowledge of the number of clusters. + +In contrast, our model proposes a novel hierarchical, non-parametric approach that: +- **Discovers social circles automatically**: Our method identifies social circles within an ego-network without requiring predefined parameters. +- **Utilizes both structural and user-attribute information**: By leveraging the principle of homophily, our approach better captures the natural grouping of characters. +- **Overcomes limitations of traditional methods**: Unlike traditional hierarchical clustering, which may fail in overlapping contexts, our method is designed to recognize and represent overlapping clusters effectively. + +Results from testing on Facebook datasets of ego-networks indicate that our approach performs comparably to benchmark results, showcasing its effectiveness in social network analysis. + +## How to Run the Code +1. Ensure you have Python 3.x and the required libraries installed. +2. Place the `star-wars-network-edges.csv` file in the `data` directory. +3. Run the script in a Jupyter notebook or a Python environment: + ```bash + Social Network Analysis.ipynb + ``` + +Feel free to modify the code for further analysis or visualizations! + +## License +This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details. +``` \ No newline at end of file diff --git a/Unsupervised Learning/Social Network Analysis/Social Network Analysis.ipynb b/Unsupervised Learning/Social Network Analysis/Social Network Analysis.ipynb new file mode 100644 index 00000000..5273a42a --- /dev/null +++ b/Unsupervised Learning/Social Network Analysis/Social Network Analysis.ipynb @@ -0,0 +1,651 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Social Network Analysis" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The building blocks of a network are *nodes* and *edges*. Nodes represent individuals in the network. They are people, tweets, firms, Twitter users, etc. They are the thing doing the interaction.\n", + "\n", + "![](img/net-1-node.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The connection between nodes are called *edges*. They imply some kind of relationship between the edges. This interaction could be friendship, mutual attendance of an event, dating, or has done business with.\n", + "\n", + "![](img/net-1-edge.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Edges can be *directed* or *undirected*. For instance, on Facebook, friendships are mutual and both parties must agree to that friendship. Therefore, it is called *undirected* because it is by definition a two-way relationship. However, on Twitter, user A can follow user B, but user B does not have to follow user A. This is called a *directed* graph because it can be a one-way relationship. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Lastly, edges can be *weighted*. Weights are usually numerical values which indicate a strength of a relationship. The edge between you and your best friend is probably higher than you and one of your classmates who you do not speak to often." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "![](http://evelinag.com/blog/2015/12-15-star-wars-social-network/star-wars-logo.png)\n", + "\n", + "In this lab we will be using a small network that indicates [interactions in the movie Star Wars Episode IV](http://evelinag.com/blog/2015/12-15-star-wars-social-network/). Here, each node is a character and each edge indicates whether they appeared together in a scene of the movie. Edges here are thus undirected and they also have weights attached, since they can appear in multiple scenes together.\n", + "\n", + "The first step is to read the list of edges in this network. For this exercise, we are going to use the [networkx](https://networkx.github.io/) module to read, analyse, and visualise the networks. " + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "#!pip install networkx\n", + "# !pip install matplotlib\n", + "# !pip install prettytable" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import networkx as nx" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will also use the matplotlib module for visualisation." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can read in the network as a weighted edgelist. This is a CSV file in the format of node1, node2, weight. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "G = nx.read_weighted_edgelist('data/star-wars-network-edges.csv', delimiter = \",\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can use a method to see all the edges in the network." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "EdgeView([('C-3PO', 'R2-D2'), ('C-3PO', 'CHEWBACCA'), ('C-3PO', 'BERU'), ('C-3PO', 'LUKE'), ('C-3PO', 'OWEN'), ('C-3PO', 'LEIA'), ('C-3PO', 'OBI-WAN'), ('C-3PO', 'HAN'), ('C-3PO', 'BIGGS'), ('C-3PO', 'RED LEADER'), ('R2-D2', 'LUKE'), ('R2-D2', 'OBI-WAN'), ('R2-D2', 'LEIA'), ('R2-D2', 'HAN'), ('R2-D2', 'CHEWBACCA'), ('R2-D2', 'DODONNA'), ('LUKE', 'CHEWBACCA'), ('LUKE', 'CAMIE'), ('LUKE', 'BIGGS'), ('LUKE', 'BERU'), ('LUKE', 'OWEN'), ('LUKE', 'LEIA'), ('LUKE', 'OBI-WAN'), ('LUKE', 'HAN'), ('LUKE', 'DODONNA'), ('LUKE', 'GOLD LEADER'), ('LUKE', 'WEDGE'), ('LUKE', 'RED LEADER'), ('LUKE', 'RED TEN'), ('OBI-WAN', 'CHEWBACCA'), ('OBI-WAN', 'LEIA'), ('OBI-WAN', 'HAN'), ('OBI-WAN', 'DARTH VADER'), ('LEIA', 'CHEWBACCA'), ('LEIA', 'DARTH VADER'), ('LEIA', 'BERU'), ('LEIA', 'MOTTI'), ('LEIA', 'TARKIN'), ('LEIA', 'HAN'), ('LEIA', 'BIGGS'), ('LEIA', 'RED LEADER'), ('HAN', 'CHEWBACCA'), ('HAN', 'GREEDO'), ('HAN', 'JABBA'), ('CHEWBACCA', 'DARTH VADER'), ('CHEWBACCA', 'DODONNA'), ('DODONNA', 'GOLD LEADER'), ('DODONNA', 'WEDGE'), ('DARTH VADER', 'MOTTI'), ('DARTH VADER', 'TARKIN'), ('CAMIE', 'BIGGS'), ('BIGGS', 'RED LEADER'), ('BIGGS', 'WEDGE'), ('BIGGS', 'GOLD LEADER'), ('BERU', 'OWEN'), ('MOTTI', 'TARKIN'), ('GOLD LEADER', 'WEDGE'), ('GOLD LEADER', 'RED LEADER'), ('WEDGE', 'RED LEADER'), ('RED LEADER', 'RED TEN')])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "G.edges()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "And we can use a similar one to see all the nodes." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "NodeView(('C-3PO', 'R2-D2', 'LUKE', 'OBI-WAN', 'LEIA', 'HAN', 'CHEWBACCA', 'DODONNA', 'DARTH VADER', 'CAMIE', 'BIGGS', 'BERU', 'OWEN', 'MOTTI', 'TARKIN', 'GREEDO', 'JABBA', 'GOLD LEADER', 'WEDGE', 'RED LEADER', 'RED TEN'))" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "G.nodes()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To see a specific attribute of an edge, we need to use get_edge_attributes. Who seems to have the highest weight in their interactions?" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{('C-3PO', 'R2-D2'): 17.0,\n", + " ('C-3PO', 'CHEWBACCA'): 5.0,\n", + " ('C-3PO', 'BERU'): 2.0,\n", + " ('C-3PO', 'LUKE'): 18.0,\n", + " ('C-3PO', 'OWEN'): 2.0,\n", + " ('C-3PO', 'LEIA'): 6.0,\n", + " ('C-3PO', 'OBI-WAN'): 6.0,\n", + " ('C-3PO', 'HAN'): 6.0,\n", + " ('C-3PO', 'BIGGS'): 1.0,\n", + " ('C-3PO', 'RED LEADER'): 1.0,\n", + " ('R2-D2', 'LUKE'): 13.0,\n", + " ('R2-D2', 'OBI-WAN'): 6.0,\n", + " ('R2-D2', 'LEIA'): 5.0,\n", + " ('R2-D2', 'HAN'): 5.0,\n", + " ('R2-D2', 'CHEWBACCA'): 3.0,\n", + " ('R2-D2', 'DODONNA'): 1.0,\n", + " ('LUKE', 'CHEWBACCA'): 16.0,\n", + " ('LUKE', 'CAMIE'): 2.0,\n", + " ('LUKE', 'BIGGS'): 4.0,\n", + " ('LUKE', 'BERU'): 3.0,\n", + " ('LUKE', 'OWEN'): 3.0,\n", + " ('LUKE', 'LEIA'): 17.0,\n", + " ('LUKE', 'OBI-WAN'): 19.0,\n", + " ('LUKE', 'HAN'): 26.0,\n", + " ('LUKE', 'DODONNA'): 1.0,\n", + " ('LUKE', 'GOLD LEADER'): 1.0,\n", + " ('LUKE', 'WEDGE'): 2.0,\n", + " ('LUKE', 'RED LEADER'): 3.0,\n", + " ('LUKE', 'RED TEN'): 1.0,\n", + " ('OBI-WAN', 'CHEWBACCA'): 7.0,\n", + " ('OBI-WAN', 'LEIA'): 1.0,\n", + " ('OBI-WAN', 'HAN'): 9.0,\n", + " ('OBI-WAN', 'DARTH VADER'): 1.0,\n", + " ('LEIA', 'CHEWBACCA'): 11.0,\n", + " ('LEIA', 'DARTH VADER'): 1.0,\n", + " ('LEIA', 'BERU'): 1.0,\n", + " ('LEIA', 'MOTTI'): 1.0,\n", + " ('LEIA', 'TARKIN'): 1.0,\n", + " ('LEIA', 'HAN'): 13.0,\n", + " ('LEIA', 'BIGGS'): 1.0,\n", + " ('LEIA', 'RED LEADER'): 1.0,\n", + " ('HAN', 'CHEWBACCA'): 19.0,\n", + " ('HAN', 'GREEDO'): 1.0,\n", + " ('HAN', 'JABBA'): 1.0,\n", + " ('CHEWBACCA', 'DARTH VADER'): 1.0,\n", + " ('CHEWBACCA', 'DODONNA'): 1.0,\n", + " ('DODONNA', 'GOLD LEADER'): 1.0,\n", + " ('DODONNA', 'WEDGE'): 1.0,\n", + " ('DARTH VADER', 'MOTTI'): 1.0,\n", + " ('DARTH VADER', 'TARKIN'): 7.0,\n", + " ('CAMIE', 'BIGGS'): 2.0,\n", + " ('BIGGS', 'RED LEADER'): 3.0,\n", + " ('BIGGS', 'WEDGE'): 2.0,\n", + " ('BIGGS', 'GOLD LEADER'): 1.0,\n", + " ('BERU', 'OWEN'): 3.0,\n", + " ('MOTTI', 'TARKIN'): 2.0,\n", + " ('GOLD LEADER', 'WEDGE'): 1.0,\n", + " ('GOLD LEADER', 'RED LEADER'): 1.0,\n", + " ('WEDGE', 'RED LEADER'): 3.0,\n", + " ('RED LEADER', 'RED TEN'): 1.0}" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nx.get_edge_attributes(G, 'weight')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we're ready to draw. We'll use the basic draw method first to illustrate the graph. " + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nx.draw(G)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This looks interesting, but we don't really know which node is which unless we add some labels. Before we add labels, we need to assign the labels particular positions on the graph." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We're going to play with two layouts. The first is a \"circular\" layout, which is useful because we can see all the nodes and the connections between them. However, with this layout, we have a harder time seeing what groups of nodes seem to cluster together." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The second layout is called \"Fruchterman-Reingold\". It is a \"force-directed\" layout, which implies that if subnetworks seem to be tied closer together, they squeeze together more in the graph. Let's play with both." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pos = nx.fruchterman_reingold_layout(G)\n", + "nx.draw_networkx_labels(G, pos)\n", + "nx.draw(G, pos)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So we're starting to see some patterns, even if we can't really see much of the text. Peripherial characters like Jabba and Greedo are only connected by one edge. However, in the center there seems to be a cluster of people like Luke, R2-D2, and Chewie." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's do the same thing with a circular layout." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pos = nx.circular_layout(G)\n", + "nx.draw_networkx_labels(G, pos)\n", + "nx.draw(G, pos)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This lets us see more of the links that exist between different nodes. It's actually not super useful, though, unless we have some more information about the edges. That's where the weights come into play." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can display the weight of the edge. We can do this by setting some levels for line weights. We can have three: small, mid, and large." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(np.float64(-1.197658037772024),\n", + " np.float64(1.2088272343584276),\n", + " np.float64(-1.2066165533189146),\n", + " np.float64(1.2066165618338638))" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## select edges by weight\n", + "esmall = [(u,v) for (u,v,d) in G.edges(data = True) if d['weight'] < 5]\n", + "emid = [(u,v) for (u,v,d) in G.edges(data = True) if d['weight'] >= 5 and d['weight'] < 10 ]\n", + "elarge = [(u,v) for (u,v,d) in G.edges(data = True) if d['weight'] >= 10]\n", + "\n", + "## draw edges in varying edge widths\n", + "nx.draw_networkx_edges(G, pos, edgelist = elarge, width = 4, alpha = 0.5)\n", + "nx.draw_networkx_edges(G, pos, edgelist = emid, width = 2, alpha = 0.5)\n", + "nx.draw_networkx_edges(G, pos, edgelist = esmall, width = 1, alpha = 0.5)\n", + "nx.draw_networkx_nodes(G, pos)\n", + "\n", + "nx.draw_networkx_labels(G, pos)\n", + "\n", + "plt.axis('off')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With this, we can see some stronger links between people like Chewie and Han, Luke and Obi-Wan." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Lastly, we can set the colours of nodes based on whether the person is on the light side, the dark side, or is other. Let's use the Fruchterman-Reingold layout because it allows us to see clusters a bit better." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(np.float64(-1.1366982946190536),\n", + " np.float64(0.9301485474296141),\n", + " np.float64(-1.1858300089879625),\n", + " np.float64(0.9556396183971299))" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "## select nodes by light side / dark side / other\n", + "dark_side = [\"DARTH VADER\", \"MOTTI\", \"TARKIN\"]\n", + "light_side = [\"R2-D2\", \"CHEWBACCA\", \"C-3PO\", \"LUKE\", \"CAMIE\", \"BIGGS\",\n", + " \"LEIA\", \"BERU\", \"OWEN\", \"OBI-WAN\", \"HAN\", \"DODONNA\",\n", + " \"GOLD LEADER\", \"WEDGE\", \"RED LEADER\", \"RED TEN\"]\n", + "other = [\"GREEDO\", \"JABBA\"]\n", + "\n", + "pos = nx.fruchterman_reingold_layout(G)\n", + "\n", + "nx.draw_networkx_edges(G, pos, edgelist = elarge, width = 4, alpha = 0.5)\n", + "nx.draw_networkx_edges(G, pos, edgelist = emid, width = 2, alpha = 0.5)\n", + "nx.draw_networkx_edges(G, pos, edgelist = esmall, width = 1, alpha = 0.5)\n", + "\n", + "## draw the nodes\n", + "nx.draw_networkx_nodes(G, pos, node_color = 'red', nodelist = dark_side)\n", + "nx.draw_networkx_nodes(G, pos, node_color = 'yellow', nodelist = light_side)\n", + "nx.draw_networkx_nodes(G, pos, node_color = 'gray', nodelist = other)\n", + "nx.draw_networkx_labels(G, pos)\n", + "\n", + "plt.axis('off')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We see some clear patterns here. The light side is very much clustered together, while the dark side has its own grouping. The outliers -- Jabba and Greedo -- aren't grouped at all." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In addition to graphing, we can create some network-level statistics which characterize the network. This includes *density*, which measures how many of the possible connections in this network have been made. If density equals 1, that would imply that everyone in the movie had a scene with everyone else." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "0.2857142857142857" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nx.density(G)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Lastly, there are node-level statistics which characterize individual nodes. One of the more important one of these is *degree*, which means how many edges are connected to this particular node. Which nodes seem to have the highest degree?" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "DegreeView({'C-3PO': 10, 'R2-D2': 7, 'LUKE': 15, 'OBI-WAN': 7, 'LEIA': 12, 'HAN': 8, 'CHEWBACCA': 8, 'DODONNA': 5, 'DARTH VADER': 5, 'CAMIE': 2, 'BIGGS': 7, 'BERU': 4, 'OWEN': 3, 'MOTTI': 3, 'TARKIN': 3, 'GREEDO': 1, 'JABBA': 1, 'GOLD LEADER': 5, 'WEDGE': 5, 'RED LEADER': 7, 'RED TEN': 2})" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nx.degree(G)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+-------------+--------+\n", + "| Node | Degree |\n", + "+-------------+--------+\n", + "| C-3PO | 10 |\n", + "| R2-D2 | 7 |\n", + "| LUKE | 15 |\n", + "| OBI-WAN | 7 |\n", + "| LEIA | 12 |\n", + "| HAN | 8 |\n", + "| CHEWBACCA | 8 |\n", + "| DODONNA | 5 |\n", + "| DARTH VADER | 5 |\n", + "| CAMIE | 2 |\n", + "| BIGGS | 7 |\n", + "| BERU | 4 |\n", + "| OWEN | 3 |\n", + "| MOTTI | 3 |\n", + "| TARKIN | 3 |\n", + "| GREEDO | 1 |\n", + "| JABBA | 1 |\n", + "| GOLD LEADER | 5 |\n", + "| WEDGE | 5 |\n", + "| RED LEADER | 7 |\n", + "| RED TEN | 2 |\n", + "+-------------+--------+\n" + ] + } + ], + "source": [ + "import networkx as nx\n", + "from prettytable import PrettyTable\n", + "\n", + "degree_view = nx.degree(G)\n", + "\n", + "table = PrettyTable()\n", + "table.field_names = [\"Node\", \"Degree\"]\n", + "\n", + "for node, degree in degree_view:\n", + " table.add_row([node, degree])\n", + "\n", + "print(table)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Interpretation\n", + "\n", + "- **Highest Degree:** LUKE has the highest degree with **15**, indicating he has the most connections with other characters in the network.\n", + "- **Other Notable Characters:** C-3PO and LEIA also have significant degrees, with **10** and **12**, respectively.\n", + "- **Low Connectivity:** Characters like GREEDO and JABBA have the lowest degree, indicating limited interactions with other characters." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.7" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/Unsupervised Learning/Social Network Analysis/data/star-wars-network-edges.csv b/Unsupervised Learning/Social Network Analysis/data/star-wars-network-edges.csv new file mode 100644 index 00000000..2ca4c656 --- /dev/null +++ b/Unsupervised Learning/Social Network Analysis/data/star-wars-network-edges.csv @@ -0,0 +1,60 @@ +C-3PO,R2-D2,17 +LUKE,R2-D2,13 +OBI-WAN,R2-D2,6 +LEIA,R2-D2,5 +HAN,R2-D2,5 +CHEWBACCA,R2-D2,3 +DODONNA,R2-D2,1 +CHEWBACCA,OBI-WAN,7 +C-3PO,CHEWBACCA,5 +CHEWBACCA,LUKE,16 +CHEWBACCA,HAN,19 +CHEWBACCA,LEIA,11 +CHEWBACCA,DARTH VADER,1 +CHEWBACCA,DODONNA,1 +CAMIE,LUKE,2 +BIGGS,CAMIE,2 +BIGGS,LUKE,4 +DARTH VADER,LEIA,1 +BERU,LUKE,3 +BERU,OWEN,3 +BERU,C-3PO,2 +LUKE,OWEN,3 +C-3PO,LUKE,18 +C-3PO,OWEN,2 +C-3PO,LEIA,6 +LEIA,LUKE,17 +BERU,LEIA,1 +LUKE,OBI-WAN,19 +C-3PO,OBI-WAN,6 +LEIA,OBI-WAN,1 +MOTTI,TARKIN,2 +DARTH VADER,MOTTI,1 +DARTH VADER,TARKIN,7 +HAN,OBI-WAN,9 +HAN,LUKE,26 +GREEDO,HAN,1 +HAN,JABBA,1 +C-3PO,HAN,6 +LEIA,MOTTI,1 +LEIA,TARKIN,1 +HAN,LEIA,13 +DARTH VADER,OBI-WAN,1 +DODONNA,GOLD LEADER,1 +DODONNA,WEDGE,1 +DODONNA,LUKE,1 +GOLD LEADER,WEDGE,1 +GOLD LEADER,LUKE,1 +LUKE,WEDGE,2 +BIGGS,LEIA,1 +LEIA,RED LEADER,1 +LUKE,RED LEADER,3 +BIGGS,RED LEADER,3 +BIGGS,C-3PO,1 +C-3PO,RED LEADER,1 +RED LEADER,WEDGE,3 +GOLD LEADER,RED LEADER,1 +BIGGS,WEDGE,2 +RED LEADER,RED TEN,1 +BIGGS,GOLD LEADER,1 +LUKE,RED TEN,1 diff --git a/Unsupervised Learning/Social Network Analysis/data/star-wars-network-nodes.csv b/Unsupervised Learning/Social Network Analysis/data/star-wars-network-nodes.csv new file mode 100644 index 00000000..8369626f --- /dev/null +++ b/Unsupervised Learning/Social Network Analysis/data/star-wars-network-nodes.csv @@ -0,0 +1,23 @@ +"name","id" +"R2-D2",0 +"CHEWBACCA",1 +"C-3PO",2 +"LUKE",3 +"DARTH VADER",4 +"CAMIE",5 +"BIGGS",6 +"LEIA",7 +"BERU",8 +"OWEN",9 +"OBI-WAN",10 +"MOTTI",11 +"TARKIN",12 +"HAN",13 +"GREEDO",14 +"JABBA",15 +"DODONNA",16 +"GOLD LEADER",17 +"WEDGE",18 +"RED LEADER",19 +"RED TEN",20 +"GOLD FIVE",21 diff --git a/Unsupervised Learning/Social Network Analysis/img/hastie_etal-f12-1.png b/Unsupervised Learning/Social Network Analysis/img/hastie_etal-f12-1.png new file mode 100644 index 0000000000000000000000000000000000000000..1a57851c62038cb308562d6c939f1f6c639dad38 GIT binary patch literal 18991 zcmdSApjZQC}dZQHhO+qP|E+O~~pPurNbZFir3_TJz7?uhT_`E@EHBeE82 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2001 From: Shreya Verma <147494302+vermu490@users.noreply.github.com> Date: Thu, 31 Oct 2024 00:00:28 +0530 Subject: [PATCH 2/2] Add Blood Donations Prediction project in Prediction Models --- .../Blood Donation Prediction.ipynb | 1277 +++++++++++++++++ .../Blood Donations Prediction/LICENSE | 21 + .../Blood Donations Prediction/README.md | 60 + .../Blood Donations Prediction/data/test.csv | 201 +++ .../Blood Donations Prediction/data/train.csv | 577 ++++++++ 5 files changed, 2136 insertions(+) create mode 100644 Prediction Models/Blood Donations Prediction/Blood Donation Prediction.ipynb create mode 100644 Prediction Models/Blood Donations Prediction/LICENSE create mode 100644 Prediction Models/Blood Donations Prediction/README.md create mode 100644 Prediction Models/Blood Donations Prediction/data/test.csv create mode 100644 Prediction Models/Blood Donations Prediction/data/train.csv diff --git a/Prediction Models/Blood Donations Prediction/Blood Donation Prediction.ipynb b/Prediction Models/Blood Donations Prediction/Blood Donation Prediction.ipynb new file mode 100644 index 00000000..d277a1c6 --- /dev/null +++ b/Prediction Models/Blood Donations Prediction/Blood Donation Prediction.ipynb @@ -0,0 +1,1277 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Predicting if a Blood Donor will donate within a given time window" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "While working for Rotaract Club of MSIT from last 3 years one of my main responsibility was to organise Blood Donation Camps, and it is an amazing event to organise because it gives you a feeling that you are helping for a right cause which saves life.\n", + "\n", + "### Problem\n", + "One of the major problem while organising the Blood Donation Camp was that to convince the people who were walking near the camp to be a donor which results in 70% of the people were not interesting in donating due to reasons like they have work to do, they need to go somewhere etc.\n", + "There's this one time in every year when we organise a blood donation camp in Adarsh Public School, New Delhi on the day of parent teacher meeting, so parents were already told about the donation camp and almost 80-90% of the parents become donors. \n", + "\n", + "So, I thought that if before organising the event we could we could reach out to the right people before the donation then we will get more donors and can save more lives. As part of making records we were collecting data of the volunteers from last 2 years and contains details of there address but it was not well organised.\n", + "\n", + "So I googled it.\n", + "\n", + "I found the data that I needed from [Drivendata](https://www.drivendata.org/competitions/2/warm-up-predict-blood-donations/data/).\n", + "\n", + "### Use information about each donor's history\n", + "- Months since Last Donation: this is the number of monthis since this donor's most recent donation.\n", + "- Number of Donations: this is the total number of donations that the donor has made.\n", + "- Total Volume Donated: this is the total amound of blood that the donor has donated in cubuc centimeters.\n", + "- Months since First Donation: this is the number of months since the donor's first donation." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Loading the Data\n", + "\n", + "The data are pre-split into training and test sets, so we’ll read them in separately. " + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# Import the libraries\n", + "import pandas as pd\n", + "import numpy as np\n", + "import seaborn as sns\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(576, 6)\n", + "id 0\n", + "months_since_last_donation 0\n", + "num_donations 0\n", + "vol_donations 0\n", + "months_since_first_donation 0\n", + "class 0\n", + "dtype: int64\n" + ] + }, + { + "data": { + "text/html": [ + "

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" + ], + "text/plain": [ + " id months_since_last_donation num_donations vol_donations \\\n", + "0 619 2 50 12500 \n", + "1 664 0 13 3250 \n", + "2 441 1 16 4000 \n", + "3 160 2 20 5000 \n", + "4 358 1 24 6000 \n", + "\n", + " months_since_first_donation class \n", + "0 98 1 \n", + "1 28 1 \n", + "2 35 1 \n", + "3 45 1 \n", + "4 77 0 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_csv('train.csv', index_col=False)\n", + "df.columns = ['id','months_since_last_donation','num_donations','vol_donations','months_since_first_donation', 'class']\n", + "test = pd.read_csv(\"test.csv\")\n", + "test.columns = ['id','months_since_last_donation','num_donations','vol_donations','months_since_first_donation']\n", + "IDtest = test[\"id\"]\n", + "print(df.shape)\n", + "print(df.isnull().sum())\n", + "df.head(5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The good thing is we have no missing values and we have 576 rows and 6 Columns. The features are 'Months since Last Donation', 'Number of Donations', 'Total Volume Donated', 'Months since First Donation'.\n", + "\n", + "In the class column there are two classes\n", + "- class 1 : The donor donated blood in March 2007.\n", + "- class 0 : The donor did not donate blood in March 2007.\n", + "\n", + "Note : I am asuming that 1 means donated and 0 means not donated" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Outliers Detection\n", + "Since outliers can have a dramatic effect on the prediction (espacially for regression problems), i choosed to manage them.\n", + "\n", + "The Tukey method (Tukey JW., 1977) is used to detect ouliers which defines an interquartile range comprised between the 1st and 3rd quartile of the distribution values (IQR). An outlier is a row that have a feature value outside the (IQR +- an outlier step).\n", + "\n", + "Detected the outliers from the numerical values features (Age, SibSp, Sarch and Fare). Then, considered outliers as rows that have at least two outlied numerical values." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# import required libraries\n", + "from collections import Counter\n", + "\n", + "# Outlier detection \n", + "def detect_outliers(df,n,features):\n", + " \"\"\"\n", + " Takes a dataframe of features and returns a list of the indices\n", + " corresponding to the observations containing more than n outliers according\n", + " to the Tukey method.\n", + " \"\"\"\n", + " outlier_indices = []\n", + " \n", + " # iterate over features(columns)\n", + " for col in features:\n", + " # 1st quartile (25%)\n", + " Q1 = np.percentile(df[col], 25)\n", + " # 3rd quartile (75%)\n", + " Q3 = np.percentile(df[col],75)\n", + " # Interquartile range (IQR)\n", + " IQR = Q3 - Q1\n", + " \n", + " # outlier step\n", + " outlier_step = 1.5 * IQR\n", + " \n", + " # Determine a list of indices of outliers for feature col\n", + " outlier_list_col = df[(df[col] < Q1 - outlier_step) | (df[col] > Q3 + outlier_step )].index\n", + " \n", + " # append the found outlier indices for col to the list of outlier indices \n", + " outlier_indices.extend(outlier_list_col)\n", + " \n", + " # select observations containing more than 2 outliers\n", + " outlier_indices = Counter(outlier_indices) \n", + " multiple_outliers = list( k for k, v in outlier_indices.items() if v > n )\n", + " \n", + " return multiple_outliers \n", + "\n", + "# detect outliers from Age, SibSp , Parch and Fare\n", + "Outliers_to_drop = detect_outliers(df,2,[\"months_since_last_donation\",\"num_donations\",\"vol_donations\",\"months_since_first_donation\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "Empty DataFrame\n", + "Columns: [id, months_since_last_donation, num_donations, vol_donations, months_since_first_donation, class]\n", + "Index: []" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Outliers in train\n", + "df.loc[Outliers_to_drop]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This is good we have no outliers issue in the data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Joining Train and Test Data\n", + "Join train and test datasets in order to obtain the same number of features during categorical conversion. This will help in feature engineering" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:2: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n", + "of pandas will change to not sort by default.\n", + "\n", + "To accept the future behavior, pass 'sort=False'.\n", + "\n", + "To retain the current behavior and silence the warning, pass 'sort=True'.\n", + "\n", + " \n" + ] + }, + { + "data": { + "text/plain": [ + "class 200\n", + "id 0\n", + "months_since_first_donation 0\n", + "months_since_last_donation 0\n", + "num_donations 0\n", + "vol_donations 0\n", + "dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "train_len = len(df)\n", + "dataset = pd.concat(objs=[df, test], axis=0).reset_index(drop=True)\n", + "# Fill empty and NaNs values with NaN\n", + "dataset = dataset.fillna(np.nan)\n", + "# Check for Null values\n", + "dataset.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " class id months_since_first_donation months_since_last_donation \\\n", + "0 1.0 619 98 2 \n", + "1 1.0 664 28 0 \n", + "2 1.0 441 35 1 \n", + "3 1.0 160 45 2 \n", + "4 0.0 358 77 1 \n", + "\n", + " num_donations vol_donations \n", + "0 50 12500 \n", + "1 13 3250 \n", + "2 16 4000 \n", + "3 20 5000 \n", + "4 24 6000 " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Correlation matrix between numerical values (SibSp Parch Age and Fare values) and Survived \n", + "g = sns.heatmap(df[[\"class\",\"months_since_last_donation\",\"num_donations\",\"months_since_first_donation\"]].corr(),annot=True, fmt = \".2f\", cmap = \"coolwarm\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Only months_since_first_donation seems to have a significative correlation with the class probability.\n", + "\n", + "It doesn't mean that the other features are not usefull. num_donations in these features can be correlated with the class. To determine this, we need to explore in detail these features." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "g = sns.FacetGrid(df, col='class')\n", + "g = g.map(sns.distplot, \"num_donations\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We notice that num_donations distributions are not the same in the class 1 and class 0 subpopulations. Indeed, there is a peak corresponding to the people who have donated only 0-1 time will not donate blood and who have donated 2-3 will likely donate.\n", + "\n", + "It seems that people have donated more number of times are more likely to donate blood." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "g = sns.FacetGrid(df, col='class')\n", + "g = g.map(sns.distplot, \"months_since_last_donation\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We notice that months_since_last_donation distributions are not the same in the class 1 and class 0 subpopulations. Indeed, there is a peak corresponding to the people who have donated recently(in 1-2 months) will donate blood.\n", + "\n", + "It seems that people have donated recently are more likely to donate blood." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "g = sns.FacetGrid(df, col='class')\n", + "g = g.map(sns.distplot, \"months_since_first_donation\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We notice that months_since_first_donation distributions are not the same in the class 1 and class 0 subpopulations. Indeed, there is a peak corresponding to the people who have just donated recently(in 6-20 months) will not donate blood." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "g = sns.FacetGrid(df, col='class')\n", + "g = g.map(sns.distplot, \"vol_donations\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Volume donated is also a good feature to know wether the donor will donate or not." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Correlation between frequency and monetary" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(15,10));\n", + "_ = sns.lmplot(x='num_donations',\n", + " y='vol_donations',\n", + " hue='class',\n", + " fit_reg=False,\n", + " data=df);\n", + "_ = plt.title(\"Correlation between frequency and monetary\");\n", + "plt.show();" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "From the graph we can see that Frequency and monetary values are highly correlated. So we can use only the frequency." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "# We do not require the volume column, so drop it.\n", + "dataset.drop(['id', 'vol_donations'], axis=1, inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Feature ENginerring\n", + "\n", + "We will create a New variable = log(“Months since First Donation”-“Months since Last Donation”)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "dataset[\"new_variable\"] = (dataset[\"months_since_first_donation\"] - dataset[\"months_since_last_donation\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Modeling" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Anaconda\\lib\\site-packages\\pandas\\core\\frame.py:3697: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n", + " errors=errors)\n" + ] + } + ], + "source": [ + "## Separate train dataset and test dataset\n", + "train = dataset[:train_len]\n", + "test = dataset[train_len:]\n", + "test.drop(labels=[\"class\"],axis = 1,inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Anaconda\\lib\\site-packages\\ipykernel_launcher.py:3: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n", + " This is separate from the ipykernel package so we can avoid doing imports until\n" + ] + } + ], + "source": [ + "## Separate train features and label \n", + "\n", + "train[\"class\"] = train[\"class\"].astype(int)\n", + "\n", + "Y_train = train[\"class\"]\n", + "\n", + "X_train = train.drop(labels = [\"class\"],axis = 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "# Feature Scaling\n", + "from sklearn.preprocessing import StandardScaler\n", + "sc = StandardScaler()\n", + "X_train_scaled = sc.fit_transform(X_train)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Cross Validation Models\n", + "I compared 10 popular classifiers and evaluate the mean accuracy of each of them by a stratified kfold cross validation procedure.\n", + "\n", + "- SVC\n", + "- Decision Tree\n", + "- AdaBoost\n", + "- Random Forest\n", + "- Extra Trees\n", + "- Gradient Boosting\n", + "- Multiple layer perceprton (neural network)\n", + "- KNN\n", + "- Logistic regression\n", + "- Linear Discriminant Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "# Import the packages\n", + "from collections import Counter\n", + "\n", + "from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier, ExtraTreesClassifier, VotingClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neural_network import MLPClassifier\n", + "from sklearn.svm import SVC\n", + "from sklearn.model_selection import GridSearchCV, cross_val_score, StratifiedKFold, learning_curve" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Cross validate model with Kfold stratified cross val\n", + "kfold = StratifiedKFold(n_splits=10)\n", + "# Modeling step Test differents algorithms \n", + "random_state = 7\n", + "classifiers = []\n", + "classifiers.append(SVC(random_state=random_state))\n", + "classifiers.append(DecisionTreeClassifier(random_state=random_state))\n", + "classifiers.append(AdaBoostClassifier(DecisionTreeClassifier(random_state=random_state),random_state=random_state,learning_rate=0.1))\n", + "classifiers.append(RandomForestClassifier(random_state=random_state))\n", + "classifiers.append(ExtraTreesClassifier(random_state=random_state))\n", + "classifiers.append(GradientBoostingClassifier(random_state=random_state))\n", + "classifiers.append(MLPClassifier(random_state=random_state))\n", + "classifiers.append(KNeighborsClassifier())\n", + "classifiers.append(LogisticRegression(random_state = random_state))\n", + "classifiers.append(LinearDiscriminantAnalysis())\n", + "\n", + "cv_results = []\n", + "for classifier in classifiers :\n", + " cv_results.append(cross_val_score(classifier, X_train_scaled, y = Y_train, scoring = \"accuracy\", cv = kfold, n_jobs=4))\n", + "\n", + "cv_means = []\n", + "cv_std = []\n", + "for cv_result in cv_results:\n", + " cv_means.append(cv_result.mean())\n", + " cv_std.append(cv_result.std())\n", + "\n", + "cv_res = pd.DataFrame({\"CrossValMeans\":cv_means,\"CrossValerrors\": cv_std,\"Algorithm\":[\"SVC\",\"DecisionTree\",\"AdaBoost\",\n", + "\"RandomForest\",\"ExtraTrees\",\"GradientBoosting\",\"MultipleLayerPerceptron\",\"KNeighboors\",\"LogisticRegression\",\"LinearDiscriminantAnalysis\"]})\n", + "\n", + "g = sns.barplot(\"CrossValMeans\",\"Algorithm\",data = cv_res, palette=\"Set3\",orient = \"h\",**{'xerr':cv_std})\n", + "g.set_xlabel(\"Mean Accuracy\")\n", + "g = g.set_title(\"Cross validation scores\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "By seeing the figure we can see that Random Forest, Extra Trees, Gradient Boosting Classifiers will work the best." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Hyperparameter tunning for best models\n", + "I performed a grid search optimization for Random Forest, Extra Trees, Gradient Boosting, SVC classifiers.\n", + "I set the \"n_jobs\" parameter to 4 since i have 4 cpu . The computation time is clearly reduced." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 10 folds for each of 288 candidates, totalling 2880 fits\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=4)]: Done 42 tasks | elapsed: 25.6s\n", + "[Parallel(n_jobs=4)]: Done 192 tasks | elapsed: 1.5min\n", + "[Parallel(n_jobs=4)]: Done 442 tasks | elapsed: 3.1min\n", + "[Parallel(n_jobs=4)]: Done 792 tasks | elapsed: 5.4min\n", + "[Parallel(n_jobs=4)]: Done 1242 tasks | elapsed: 8.4min\n", + "[Parallel(n_jobs=4)]: Done 1792 tasks | elapsed: 11.8min\n", + "[Parallel(n_jobs=4)]: Done 2442 tasks | elapsed: 16.0min\n", + "[Parallel(n_jobs=4)]: Done 2880 out of 2880 | elapsed: 18.9min finished\n" + ] + }, + { + "data": { + "text/plain": [ + "0.7204861111111112" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# RFC Parameters tunning \n", + "RFC = RandomForestClassifier()\n", + "\n", + "\n", + "## Search grid for optimal parameters\n", + "rf_param_grid = {\"max_depth\": [80, 90, 100, 110],\n", + " \"max_features\": [2, 3],\n", + " \"min_samples_split\": [8, 10, 12],\n", + " \"min_samples_leaf\": [3, 4, 5],\n", + " \"bootstrap\": [False],\n", + " \"n_estimators\" :[100, 200, 300, 1000],\n", + " \"criterion\": [\"gini\"]}\n", + "\n", + "\n", + "gsRFC = GridSearchCV(RFC,param_grid = rf_param_grid, cv=kfold, scoring=\"accuracy\", n_jobs= 4, verbose = 1)\n", + "\n", + "gsRFC.fit(X_train_scaled,Y_train)\n", + "\n", + "RFC_best = gsRFC.best_estimator_\n", + "\n", + "# Best score\n", + "gsRFC.best_score_" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 10 folds for each of 72 candidates, totalling 720 fits\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=4)]: Done 42 tasks | elapsed: 19.1s\n", + "[Parallel(n_jobs=4)]: Done 192 tasks | elapsed: 1.1min\n", + "[Parallel(n_jobs=4)]: Done 442 tasks | elapsed: 2.5min\n", + "[Parallel(n_jobs=4)]: Done 720 out of 720 | elapsed: 4.0min finished\n" + ] + }, + { + "data": { + "text/plain": [ + "0.7604166666666666" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#ExtraTrees \n", + "ExtC = ExtraTreesClassifier()\n", + "\n", + "\n", + "## Search grid for optimal parameters\n", + "ex_param_grid = {\"max_depth\": [None],\n", + " \"max_features\": [2, 3],\n", + " \"min_samples_split\": [2, 3, 10],\n", + " \"min_samples_leaf\": [1, 3, 10],\n", + " \"bootstrap\": [False],\n", + " \"n_estimators\" :[100, 200, 300, 1000],\n", + " \"criterion\": [\"gini\"]}\n", + "\n", + "\n", + "gsExtC = GridSearchCV(ExtC,param_grid = ex_param_grid, cv=kfold, scoring=\"accuracy\", n_jobs= 4, verbose = 1)\n", + "\n", + "gsExtC.fit(X_train_scaled,Y_train)\n", + "\n", + "ExtC_best = gsExtC.best_estimator_\n", + "\n", + "# Best score\n", + "gsExtC.best_score_" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 10 folds for each of 72 candidates, totalling 720 fits\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=4)]: Done 42 tasks | elapsed: 7.2s\n", + "[Parallel(n_jobs=4)]: Done 192 tasks | elapsed: 13.5s\n", + "[Parallel(n_jobs=4)]: Done 442 tasks | elapsed: 24.4s\n", + "[Parallel(n_jobs=4)]: Done 720 out of 720 | elapsed: 35.9s finished\n" + ] + }, + { + "data": { + "text/plain": [ + "0.7829861111111112" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Gradient boosting tunning\n", + "\n", + "GBC = GradientBoostingClassifier()\n", + "gb_param_grid = {'loss' : [\"deviance\"],\n", + " 'n_estimators' : [100,200,300],\n", + " 'learning_rate': [0.1, 0.05, 0.01],\n", + " 'max_depth': [4, 8],\n", + " 'min_samples_leaf': [100,150],\n", + " 'max_features': [0.3, 0.1] \n", + " }\n", + "\n", + "gsGBC = GridSearchCV(GBC,param_grid = gb_param_grid, cv=kfold, scoring=\"accuracy\", n_jobs= 4, verbose = 1)\n", + "\n", + "gsGBC.fit(X_train_scaled,Y_train)\n", + "\n", + "GBC_best = gsGBC.best_estimator_\n", + "\n", + "# Best score\n", + "gsGBC.best_score_" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 10 folds for each of 28 candidates, totalling 280 fits\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=4)]: Done 47 tasks | elapsed: 6.5s\n", + "[Parallel(n_jobs=4)]: Done 273 out of 280 | elapsed: 23.3s remaining: 0.5s\n", + "[Parallel(n_jobs=4)]: Done 280 out of 280 | elapsed: 25.1s finished\n" + ] + }, + { + "data": { + "text/plain": [ + "0.765625" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "### SVC classifier\n", + "SVMC = SVC(probability=True)\n", + "svc_param_grid = {'kernel': ['rbf'], \n", + " 'gamma': [ 0.001, 0.01, 0.1, 1],\n", + " 'C': [1, 10, 50, 100,200,300, 1000]}\n", + "\n", + "gsSVMC = GridSearchCV(SVMC,param_grid = svc_param_grid, cv=kfold, scoring=\"accuracy\", n_jobs= 4, verbose = 1)\n", + "\n", + "gsSVMC.fit(X_train_scaled,Y_train)\n", + "\n", + "SVMC_best = gsSVMC.best_estimator_\n", + "\n", + "# Best score\n", + "gsSVMC.best_score_" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot learning curve\n", + "def plot_learning_curve(estimator, title, X, y, ylim=None, cv=None,\n", + " n_jobs=-1, train_sizes=np.linspace(.1, 1.0, 5)):\n", + " \"\"\"Generate a simple plot of the test and training learning curve\"\"\"\n", + " plt.figure()\n", + " plt.title(title)\n", + " if ylim is not None:\n", + " plt.ylim(*ylim)\n", + " plt.xlabel(\"Training examples\")\n", + " plt.ylabel(\"Score\")\n", + " train_sizes, train_scores, test_scores = learning_curve(\n", + " estimator, X, y, cv=cv, n_jobs=n_jobs, train_sizes=train_sizes)\n", + " train_scores_mean = np.mean(train_scores, axis=1)\n", + " train_scores_std = np.std(train_scores, axis=1)\n", + " test_scores_mean = np.mean(test_scores, axis=1)\n", + " test_scores_std = np.std(test_scores, axis=1)\n", + " plt.grid()\n", + "\n", + " plt.fill_between(train_sizes, train_scores_mean - train_scores_std,\n", + " train_scores_mean + train_scores_std, alpha=0.1,\n", + " color=\"r\")\n", + " plt.fill_between(train_sizes, test_scores_mean - test_scores_std,\n", + " test_scores_mean + test_scores_std, alpha=0.1, color=\"g\")\n", + " plt.plot(train_sizes, train_scores_mean, 'o-', color=\"r\",\n", + " label=\"Training score\")\n", + " plt.plot(train_sizes, test_scores_mean, 'o-', color=\"g\",\n", + " label=\"Cross-validation score\")\n", + "\n", + " plt.legend(loc=\"best\")\n", + " return plt\n", + "\n", + "g = plot_learning_curve(gsRFC.best_estimator_,\"RF mearning curves\",X_train,Y_train,cv=kfold)\n", + "g = plot_learning_curve(gsExtC.best_estimator_,\"ExtraTrees learning curves\",X_train,Y_train,cv=kfold)\n", + "g = plot_learning_curve(gsGBC.best_estimator_,\"GradientBoosting learning curves\",X_train,Y_train,cv=kfold)\n", + "g = plot_learning_curve(gsSVMC.best_estimator_,\"SVC learning curves\",X_train,Y_train,cv=kfold)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " By looking at the learning curve GradientBoosting and ExtraTrees classifiers tend to overfit the training set. According to the growing cross-validation curves Random Forest classifier and SVC seems to better generalize the prediction since the training and cross-validation curves are close together." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Testing the models on test set\n", + "\n", + "So the we will use SVC classifier as a final model." + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "# Scaling the test data\n", + "test_scaled = sc.transform(test)\n", + "# predicting the results\n", + "predictions = gsSVMC.predict_proba(test_scaled)\n", + "predictions = predictions[:,1]\n", + "pred_report = pd.DataFrame(predictions.tolist(),index=IDtest,columns=[\"Made Donation in March 2007\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "# saving the prediction\n", + "pred_report.to_csv(\"final_submission.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conclusion" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we can target the people who are interested in donating blood and which will results in getting more volunteers and we can save more people.\n", + "\n", + "For those interested, the Jupyter Notebook with all the code can be found in the [Github repository](https://github.com/souvikb07/Predict-Blood-Donations) for this post." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Prediction Models/Blood Donations Prediction/LICENSE b/Prediction Models/Blood Donations Prediction/LICENSE new file mode 100644 index 00000000..614f13e8 --- /dev/null +++ b/Prediction Models/Blood Donations Prediction/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2018 Souvik Banerjee + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/Prediction Models/Blood Donations Prediction/README.md b/Prediction Models/Blood Donations Prediction/README.md new file mode 100644 index 00000000..d2bb44c8 --- /dev/null +++ b/Prediction Models/Blood Donations Prediction/README.md @@ -0,0 +1,60 @@ +# Predict-Blood-Donations [![](https://img.shields.io/github/license/sourcerer-io/hall-of-fame.svg?colorB=ff0000)](https://github.com/souvikb07/Predict-Blood-Donations/blob/master/LICENSE) [![](https://img.shields.io/badge/Souvik-Banerjee-blue.svg)](https://souvikb07.github.io) + + + +## Problem +Predicting if a Blood Donor will donate within a given time window? + +### Application +By solving this problem the blood donation camps can get 40% more blood donors. + +### Sourcerer +[![](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/images/0)](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/links/0)[![](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/images/1)](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/links/1)[![](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/images/2)](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/links/2)[![](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/images/3)](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/links/3)[![](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/images/4)](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/links/4)[![](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/images/5)](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/links/5)[![](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/images/6)](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/links/6)[![](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/images/7)](https://sourcerer.io/fame/souvikb07/souvikb07/Predict-Blood-Donations/links/7) + +### Code Requirements +The example code is in Python ([version 3.6.6](https://www.python.org/downloads/release/python-366/) or higher will work). + +### Dependencies + +1) import pandas +2) import numpy +3) import seaborn +4) import matplotlib +5) import Counter +6) import sklearn + +## Description + +Use Python to explore data related to blood donors and we want to predict whether or not a donor will give blood the next time when the blood donation will be organised. + +* This process will be done using a Jupyter Notebook. +* The code should run w/o errors. +* Appropriate use of + * data structures/types + * loops/conditional statements + * Packages + * functions + * coding practices (i.e. Docstrings, comments, variable names & general + readability) +* Analysis + * Pose questions about the data + * Inspect the structure of the original data (very important) + * Clean the data + * Answer questions about the data using descriptive statistics + * Visualize the data (using plt and seaborn) + * Perform additional exploratory analysis + * Consider where data analysis can be applied to other fields. +* Feature Engineering + * Using domain knowledge of the data to create features that make machine learning algorithms work. +* Machine Learning + * Use of Random Forest, Extra Trees, Gradient Boosting, SVC classifiers. + +## File Descriptions + +* ./data/ contains the various datasets. +* ./Blood Donation Prediction.ipynb is a Jupyter notebook containing the work I have done. + +## References & Citations + +1. Data provided by: + * [drivendata.org](https://www.drivendata.org/competitions/2/warm-up-predict-blood-donations/data/) diff --git a/Prediction Models/Blood Donations Prediction/data/test.csv b/Prediction Models/Blood Donations Prediction/data/test.csv new file mode 100644 index 00000000..68d00c97 --- /dev/null +++ b/Prediction Models/Blood Donations Prediction/data/test.csv @@ -0,0 +1,201 @@ +,Months since Last Donation,Number of Donations,Total Volume Donated (c.c.),Months since First Donation +659,2,12,3000,52 +276,21,7,1750,38 +263,4,1,250,4 +303,11,11,2750,38 +83,4,12,3000,34 +500,3,21,5250,42 +530,4,2,500,4 +244,14,1,250,14 +249,23,2,500,87 +728,14,4,1000,64 +129,13,3,750,16 +534,11,7,1750,62 +317,5,11,2750,75 +401,4,1,250,4 +696,4,4,1000,26 +192,11,1,250,11 +176,11,6,1500,26 +571,7,14,3500,48 +139,23,14,3500,93 +423,3,4,1000,29 +563,2,7,1750,29 +56,4,6,1500,35 +528,5,7,1750,26 +101,4,1,250,4 +467,2,3,750,38 +382,5,14,3500,86 +466,2,2,500,11 +294,14,1,250,14 +512,4,3,750,16 +659,2,12,3000,52 +389,4,14,3500,86 +487,23,7,1750,88 +701,2,1,250,2 +419,4,7,1750,58 +536,4,2,500,41 +240,11,7,1750,29 +508,2,2,500,41 +515,14,1,250,14 +283,4,6,1500,28 +650,4,1,250,4 +65,2,2,500,4 +228,16,6,1500,35 +741,16,6,1500,81 +297,2,5,1250,26 +464,14,3,750,31 +63,2,1,250,2 +231,4,4,1000,14 +28,14,3,750,35 +248,14,1,250,14 +357,14,5,1250,28 +300,2,14,3500,57 +726,5,24,6000,79 +680,14,4,1000,23 +520,4,6,1500,39 +254,23,2,500,38 +582,11,8,2000,52 +143,2,7,1750,77 +98,4,5,1250,11 +1,2,4,1000,35 +221,2,15,3750,64 +352,4,1,250,4 +64,11,2,500,38 +138,12,15,3750,71 +745,2,13,3250,76 +64,11,2,500,38 +688,16,2,500,27 +623,9,4,1000,65 +289,21,16,4000,64 +174,7,10,2500,47 +690,4,1,250,4 +105,11,5,1250,35 +427,16,4,1000,23 +48,38,1,250,38 +14,4,1,250,4 +657,23,4,1000,52 +301,11,7,1750,64 +455,14,3,750,28 +579,4,11,2750,78 +722,16,4,1000,33 +98,4,5,1250,11 +491,38,1,250,38 +303,11,11,2750,38 +466,2,2,500,11 +65,2,2,500,4 +300,2,14,3500,57 +9,21,1,250,21 +622,11,1,250,11 +323,16,2,500,26 +289,21,16,4000,64 +568,2,4,1000,26 +290,4,1,250,4 +156,4,2,500,52 +464,14,3,750,31 +426,16,2,500,16 +306,16,11,2750,40 +4,11,11,2750,42 +12,4,5,1250,23 +187,11,12,3000,58 +406,23,8,2000,64 +96,4,2,500,4 +509,2,1,250,2 +733,11,6,1500,58 +548,21,3,750,35 +478,7,5,1250,35 +501,11,2,500,16 +127,2,4,1000,11 +199,15,16,4000,82 +299,2,10,2500,49 +162,4,1,250,4 +235,16,3,750,21 +23,9,2,500,16 +473,4,1,250,4 +487,23,7,1750,88 +683,4,8,2000,28 +303,11,11,2750,38 +309,23,3,750,48 +569,23,1,250,23 +34,4,7,1750,28 +686,4,16,4000,38 +84,2,2,500,23 +733,11,6,1500,58 +537,4,9,2250,26 +181,11,4,1000,34 +453,0,26,6500,76 +67,2,10,2500,52 +161,2,16,4000,81 +307,4,6,1500,46 +703,11,2,500,11 +181,11,4,1000,34 +246,14,2,500,14 +316,3,5,1250,26 +278,11,1,250,11 +346,11,3,750,15 +545,4,1,250,4 +419,4,7,1750,58 +694,4,2,500,4 +622,11,1,250,11 +663,11,3,750,76 +262,2,13,3250,32 +461,2,12,3000,98 +373,2,34,8500,77 +233,4,1,250,4 +466,2,2,500,11 +207,2,7,1750,77 +263,4,1,250,4 +16,23,1,250,23 +513,23,3,750,35 +449,4,5,1250,33 +429,23,3,750,62 +701,2,1,250,2 +632,21,2,500,41 +529,2,9,2250,22 +245,11,9,2250,33 +344,16,6,1500,40 +353,16,3,750,19 +241,8,15,3750,77 +633,16,1,250,16 +624,2,1,250,2 +726,5,24,6000,79 +189,11,1,250,11 +138,12,15,3750,71 +402,14,1,250,14 +511,4,6,1500,23 +590,9,9,2250,16 +334,2,3,750,52 +447,16,3,750,50 +119,2,2,500,11 +389,4,14,3500,86 +644,4,1,250,4 +423,3,4,1000,29 +131,23,1,250,23 +405,40,1,250,40 +82,4,1,250,4 +643,2,41,10250,98 +156,4,2,500,52 +617,21,3,750,38 +574,2,3,750,9 +272,2,12,3000,95 +613,11,2,500,52 +545,4,1,250,4 +685,14,1,250,14 +570,11,5,1250,33 +537,4,9,2250,26 +691,16,1,250,16 +85,4,16,4000,70 +483,14,2,500,14 +455,14,3,750,28 +93,11,1,250,11 +744,2,1,250,2 +33,14,2,500,14 +321,4,23,5750,58 +523,6,3,750,26 +426,16,2,500,16 +196,14,2,500,29 +301,11,7,1750,64 +103,16,1,250,16 +224,21,2,500,23 +454,23,8,2000,46 +585,23,2,500,28 +154,4,11,2750,64 diff --git a/Prediction Models/Blood Donations Prediction/data/train.csv b/Prediction Models/Blood Donations Prediction/data/train.csv new file mode 100644 index 00000000..275fd8a3 --- /dev/null +++ b/Prediction Models/Blood Donations Prediction/data/train.csv @@ -0,0 +1,577 @@ +,Months since Last Donation,Number of Donations,Total Volume Donated (c.c.),Months since First Donation,Made Donation in March 2007 +619,2,50,12500,98,1 +664,0,13,3250,28,1 +441,1,16,4000,35,1 +160,2,20,5000,45,1 +358,1,24,6000,77,0 +335,4,4,1000,4,0 +47,2,7,1750,14,1 +164,1,12,3000,35,0 +736,5,46,11500,98,1 +436,0,3,750,4,0 +460,2,10,2500,28,1 +285,1,13,3250,47,0 +499,2,6,1500,15,1 +356,2,5,1250,11,1 +40,2,14,3500,48,1 +191,2,15,3750,49,1 +638,2,6,1500,15,1 +345,2,3,750,4,1 +463,2,3,750,4,1 +372,4,11,2750,28,0 +8,2,6,1500,16,1 +539,2,6,1500,16,1 +734,4,14,3500,40,0 +573,4,6,1500,14,0 +482,4,8,2000,21,0 +330,1,14,3500,58,0 +222,4,10,2500,28,1 +175,4,10,2500,28,1 +606,2,16,4000,64,0 +340,2,8,2000,28,1 +298,2,12,3000,47,1 +459,4,6,1500,16,1 +92,4,7,1750,22,1 +446,2,13,3250,53,1 +336,2,5,1250,16,0 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