Data

Binary classification, Regression, Multiclass classification

The following models have similar JSON structure: Binary classification, Logistic regression, Multiclass classification

{
    "data": {
        "predict_values": [
            [
                {"alias": "Lead Source", "selectedValue":"bing"},
                {"alias": "Lead Origin","selectedValue": "API"},
                {"alias": "Converted", "selectedValue": "YES"}
            ],
            [
                {"alias": "Lead Source", "selectedValue":"Google"},
                {"alias": "Lead Origin","selectedValue": "Landing Page Submission"},
                {"alias": "Converted", "selectedValue": "YES"}
            ],
            [
                {"alias": "Lead Source", "selectedValue":"Olark Chat"},
                {"alias": "Lead Origin","selectedValue": "API"},
                {"alias": "Converted", "selectedValue": "YES"}
            ]
        ]
    }
}

JSON structure represents a data object with a key "data" mapping to an array called "predict_values". The "predict_values" array contains multiple elements, each representing a set of data. Each set of data is represented as an array of objects. Each object within the array represents a key-value pair, where required "alias" is the key and required "selectedValue" is the corresponding value. The keys "Lead Source", "Lead Origin", and "Converted" are common in each object, but their values differ, representing different attributes or properties of the data. Timeseries model

{
    "data": {
        "predict_values": 
            {"startDate":"2023-04-17", "endDate":"2023-04-18", "sequenceID": "A"}
    }
}

JSON structure represents a data object with a key "data" mapping to an object called "predict_values". The "predict_values" object contains three key-value pairs. The required keys are "startDate", "endDate", and "sequenceID", and their corresponding values are "2023-04-17", "2023-04-18", and "A" respectively.