K-Nearest Neighbors - KNN (ML_CN_2)

This function finds the K number of training examples closest (nearest neighbors) to the input data and then classifying the input data based on the majority class of its nearest neighbors.

In other words, it assigns a label to a new data point based on how similar it is to the existing data points, where similarity is defined by distance metric such as Euclidean or Manhattan.

This function can be used for both supervised and unsupervised learning.

Sample Request

Build a KNN model named, "ClassicModel"

{
    "project_id": 1,
    "parent_id": 7,
    "block_id": 8,
    "function_code": "ML_CN_2",
    "args": {
        "model_name": "ClassicModel",
        "random_state": 0,
        "n_neighbors": 5,
        "distance": "minkowski",
        "p": 2
    }
}

Building a K-Nearest Neighbors model

K-Nearest Neighbors

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

Request Body

{
    "status": "true",
    "message": {
        "id": 8,
        "project": 1,
        "block_id": 8,
        "parent_id": 7,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": "{\"ClassicModel\": {\"function_code\": \"ML_R_3\", \"model_url\": ""}}"
    }
}
// Some code

Sample Request

Make predictions with the pre-built model passing an optional test data.

{
    "project_id": 1,
    "parent_id": 8,
    "block_id": 9,
    "function_code": "ML_CN_2_P",
    "args": {
        "model_name": "ClassicModel",
        "test_data": ""
    }
}

Predicting with K-Nearest Neighbors

K-Nearest Neighbors Predict

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

Request Body

{
    "status": "true",
    "message": {
        "id": 9,
        "project": 1,
        "block_id": 9,
        "parent_id": 8,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": "{\"y_pred_url\": ""}"
    }
}
// Some code

Sample Request

Evaluate model metrics

{
    "project_id": 1,
    "parent_id": 8,
    "block_id": 9,
    "function_code": "ML_CN_2_M",
    "args": {
        "model_name": "ClassicModel"
    }
}

K-Nearest Neighbors Metrics

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

Request Body

{
    "status": "true",
    "message": {
        "id": 1,
        "project": 12,
        "block_id": 10,
        "parent_id": 11,
        "dataset_url": "",
        "x_value_url": "",
        "y_value_url": "",
        "x_train_url": "",
        "y_train_url": "",
        "x_test_url": "",
        "y_test_url": "",
        "output": "{'confusion_matrix': '', 'accuracy': 0.9}"
    }
}
// Some code

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