AutoRegression (AUTO_R_1)

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 an AutoRegression model named, "AutoRegression"

{
    "project_id": 1,
    "parent_id": 7,
    "block_id": 8,
    "function_code": "AUTO_R_1",
    "args": {
        "model_name": "AutoRegression",
        "time_left": 60,
        "run_time_limit": 30,
        "n_jobs": 1
    }
}

Building a AutoRegression model

AutoRegression

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

Request Body

Name
Type
Description

project_id*

int

The id of the current project

block_id*

int

The id of the current block

function_code*

string

The function code for current block

parent_id*

int

The id of the previous block

args*

object

Block arguments

model_name*

String

Name of the model to be used for prediction.

{
    "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\": ""}}"
    }
}

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": "AUTO_R_1_P",
    "args": {
        "model_name": "AutoRegressionAutoRegression"
    }
}

Predicting with AutoRegression

XGBoost Predict

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

Request Body

Name
Type
Description

model_name*

String

Name of previously trained model to be used for prediction

test_data

String

Input data for prediction. Defaults to x_train_url in StateManagment

project_id*

int

ID of the current project

block_id*

int

ID of the current block

parent_id*

int

ID of the previous block

function_code*

String

Function code for the current block

{
    "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\": ""}"
    }
}

Sample Request

Evaluate model metrics

{
    "project_id": 1,
    "parent_id": 8,
    "block_id": 9,
    "function_code": "AUTO_R_1_M",
    "args": {
        "model_name": "AutoRegression",
        "metric": "mae"
    }
}

AutoRegression Metrics

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

Request Body

Name
Type
Description

project_id*

int

ID of the current project

parent_id*

int

ID of the previous block

block_id*

int

ID of the current block

function_code*

String

Function code for the current block

model_name*

String

Name of the pre-trained model to be used for evaluation

{
    "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}"
    }
}
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