manifest.json

{
    "title": "MultiHMM",
    "description": "Implementation of https://doi.org/10.1016/j.asoc.2017.06.035",
    "inputDimensionality": "multivariate",
    "version": "0.3.0",
    "authors": "Jinbo Li, Witold Pedrycz, Iqbal Jamal",
    "language": "Python",
    "type": "Detector",
    "learningType": "Supervised",
    "mainFile": "algorithm.py",
    "trainingStep": {
      "parameters": [
        {
          "name": "discretizer",
          "type": "enum[sugeno,choquet,fcm]",
          "defaultValue": "fcm",
          "optional": "true",
          "description": "Available discretizers are \"sugeno\", \"choquet\", and \"fcm\". If only 1 feature in time series, K-Bins discretizer is used."
        },
        {
          "name": "n_bins",
          "type": "int",
          "defaultValue": 10,
          "optional": "true",
          "description": "Number of bins used for discretization."
        },
        {
          "name": "random_state",
          "type": "int",
          "defaultValue": 42,
          "optional": "true",
          "description": "Seed for random number generation."
        }
      ],
      "modelInput": "none"
    },
    "executionStep": {
      "parameters": [
        {
          "name": "random_state",
          "type": "int",
          "defaultValue": 42,
          "optional": "true",
          "description": "Seed for random number generation."
        }
      ],
      "modelInput": "required"
    }
}