Commands model:gmm/train

Creates a GMM Model from the train frame.

POST /v1/commands/

GET /v1/commands/:id

Request

Route

POST /v1/commands/

Body

name:

model:gmm/train

arguments:

model : Model

<Missing Description>

frame : Frame

A frame to train the model on.

observation_columns : list

Columns containing the observations.

column_scalings : list

Column scalings for each of the observation columns. The scaling value is multiplied by the corresponding value in the observation column.

k : int32 (default=2)

Desired number of clusters. Default is 2.

max_iterations : int32 (default=100)

Number of iterations for which the algorithm should run. Default is 100.

convergence_tol : float64 (default=0.01)

Largest change in log-likelihood at which convergence iis considered to have occurred.

seed : int64 (default=4729768646873607665)

Random seed

Headers

Authorization: test_api_key_1
Content-type: application/json

Description

At training the ‘k’ cluster centers are computed.

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

dict

Returns a dictionary the following fields

cluster_size

: dict

with the key being a string of the form ‘Cluster:Id’ storing the number of elements in cluster number ‘Id’

gaussians

: dict

Stores the ‘mu’ and ‘sigma’ corresponding to the Multivariate Gaussian (Normal) Distribution for each Gaussian