Commands model:linear_regression/train

Build linear regression model.

POST /v1/commands/

GET /v1/commands/:id

Request

Route

POST /v1/commands/

Body

name:

model:linear_regression/train

arguments:

model : Model

<Missing Description>

frame : Frame

A frame to train the model on

value_column : unicode

Column name containing the value for each observation.

observation_columns : list

List of column(s) containing the observations.

elastic_net_parameter : float64 (default=0.0)

Parameter for the ElasticNet mixing. Default is 0.0

fit_intercept : bool (default=True)

Parameter for whether to fit an intercept term. Default is true

max_iterations : int32 (default=100)

Parameter for maximum number of iterations. Default is 100

reg_param : float64 (default=0.0)

Parameter for regularization. Default is 0.0

standardization : bool (default=True)

Parameter for whether to standardize the training features before fitting the model. Default is true

tolerance : float64 (default=1e-06)

Parameter for the convergence tolerance for iterative algorithms. Default is 1E-6

Headers

Authorization: test_api_key_1
Content-type: application/json

Description

Creating a LinearRegression Model using the observation column and target column of the train frame

Response

Status

200 OK

Body

Returns information about the command. See the Response Body for Get Command here below. It is the same.

GET /v1/commands/:id

Request

Route

GET /v1/commands/18

Body

(None)

Headers

Authorization: test_api_key_1
Content-type: application/json

Response

Status

200 OK

Body

dict

Trained linear regression model