Polynomial Linear Regression (ML_R_3)

This function uses the relationship between variables to find the best non-linear fit through the data points.

It does this by fitting a polynomial equation to the data, rather than a straight line. The degree of the polynomial equation can be adjusted to improve the fit of the model to the data.

This approach can be useful when the relationship between the variables is more complex than a simple linear relationship.

Sample Request

Build a multiple linear regression model named, "PolyModel"

{
    "project_id": 1,
    "parent_id": 7,
    "block_id": 8,
    "function_code": "ML_R_3",
    "args": {
        "model_name": "SimpleModel",
        "degree": 2
    }
}

Building a Polynomial Linear Regression model

Polynomial Linear Regression

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.
degree	int	maximum degree of polynomial features (defaults to 2)

200 Statemanagement object

{
    "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": "{\"SimpleModel\": {\"function_code\": \"ML_R_3\", \"model_url\": ""}}"
    }
}

Python

// Some code

Node

const project_id = 1
const parent_id = 7
const block_id = 8

polynomialLinearRegression = await client.polynomial_linear_regression(project_id, parent_id, block_id, {
    model_name: "SimpleModel",
    degree: 2
});

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_R_3_P",
    "args": {
        "model_name": "SimpleModel",
        "test_data": ""
    }
}

Predicting with Polynomial Linear Regression

Multiple Linear Regression 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

200: OK Statemanagement object

{
    "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\": ""}"
    }
}

Python

// Some code

Node

const project_id = 1
const parent_id = 7
const block_id = 8

polynomialLinearRegressionPredict = await client.polynomial_linear_regression_predict(project_id, parent_id, block_id, {
       model_name: "SimpleModel",
      test_data: ""
    });