8. Logistic Regression - How Well Does Medicare Data Predict an ED Visit.ipynb

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    "### Unit 8: Logistic Regression - How Well Does Medicare Data Predict an ED Visit?\n",
    "\n",
    "Kyle P. Rasku MS BSN RN\n",
    "\n",
    "In this notebook we'll a derivitive of the DE-SynPUF data - a realistic, synthetic Medicare data set created in 2013 - to try to predict ED visits.  We'll look at how to choose the variables that go into a predictive logistic regression model, and evaluate its performance using both AUC / ROC curve and a confusion matrix.\n",
    "\n",
    "Reference: Gillingham, M. (2014). SAS Programming with Medicare Administrative Data. United States: SAS Institute. https://www.google.com/books/edition/_/WniOAwAAQBAJ?hl=en"
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    "%matplotlib inline\n",
    "import matplotlib.pylab as plt\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
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      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
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      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'google.colab'"
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    "!pip install -U -q PyDrive\n",
    "from pydrive.auth import GoogleAuth\n",
    "from pydrive.drive import GoogleDrive\n",
    "from google.colab import auth\n",
    "from oauth2client.client import GoogleCredentials"
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