manifest.json

{
    "title": "DSPOT",
    "description": "Implementation of https://doi.org/10.1145/3097983.3098144.",
    "inputDimensionality": "univariate",
    "version": "0.3.0",
    "authors": "Alban Siffer, Pierre-Alain Fouque, Alexandre Termier, Christine Largouët",
    "language": "Python",
    "type": "Detector",
    "learningType": "Unsupervised",
    "mainFile": "algorithm.py",
    "executionStep": {
    	"parameters": [
            {
                "name": "q",
                "type": "float",
                "defaultValue": 1e-3,
                "optional": "true",
                "description": "Main parameter: maximum probability of an abnormal event"
            },{
                "name": "n_init",
                "type": "int",
                "defaultValue": 1000,
                "optional": "true",
                "description": "Calibration: number of data used to calibrate algorithm. The user must ensure that n_init * (1 - level) > 10"
            },{
                "name": "level",
                "type": "float",
                "defaultValue": 0.99,
                "optional": "true",
                "description": "Calibration: proportion of initial data (n_init) not involved in the tail distribution fit during initialization. The user must ensure that n_init * (1 - level) > 10"
            },{
                "name": "up",
                "type": "boolean",
                "defaultValue": "true",
                "optional": "true",
                "description": "Compute upper thresholds"
            },{
                "name": "down",
                "type": "boolean",
                "defaultValue": "true",
                "optional": "true",
                "description": "Compute lower thresholds"
            },{
                "name": "alert",
                "type": "boolean",
                "defaultValue": "true",
                "optional": "true",
                "description": "Enable alert triggering, if false, even out-of-bounds-data will be taken into account for tail fit"
            },{
                "name": "bounded",
                "type": "boolean",
                "defaultValue": "true",
                "optional": "true",
                "description": "Performance: enable memory bounding (also improves performance)"
            },{
                "name": "max_excess",
                "type": "int",
                "defaultValue": 200,
                "optional": "true",
                "description": "Performance: maximum number of data stored to perform the tail fit when memory bounding is enabled"
            },
            {
              "name": "random_state",
              "type": "int",
              "defaultValue": 42,
              "optional": "true",
              "description": "Seed for the random number generator"
            }
        ],
        "modelInput": "none"
    }
}