Feature Scaling (DP_5)

This functionality normalizes the range of values for different features in the dataset

This process is very important because many machine learning algorithms use the Euclidean distance between two points in their computations, and if the ranges of the features are vastly different, then the algorithm will be sensitive to the feature with the larger range, and may produce unexpected results.

Sample Request

This request scales the feature sets defined in the range of columns for training and testing.

{
    "project_id": 1,
    "parent_id": 4,
    "block_id": 5,
    "function_code": "DP_5",
    "args": {
        "dataset": true,
        "xtrain": true,
        "xtest": true,
        "x": true,
        "ytrain": true,
        "ytest": true,
        "y": true,
        "scaler": "maxabs",
        "boundariestoscale": ":, 2:",
        "save_name": "testweights",
        "load_name": "testweights"
    }
}

Missing Data

Encode categorical values

POST https://autogon.ai/api/v1/engine/start

Encodes categorical data on specific columns with specified boundaries

Request Body

{
    "status": "true",
    "message": {
        "id": 3,
        "project": 1,
        "block_id": 3,
        "parent_id": 2,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": ""
    }
}
// Some code

Last updated