Commands model:libsvm/test

[ALPHA] Predict test frame labels and return metrics.

POST /v1/commands/

GET /v1/commands/:id

Request

Route

POST /v1/commands/

Body

name:

model:libsvm/test

arguments:

model : <bound method AtkEntityType.__name__ of <trustedanalytics.rest.jsonschema.AtkEntityType object at 0x7f9e68702090>>

<Missing Description>

frame : <bound method AtkEntityType.__name__ of <trustedanalytics.rest.jsonschema.AtkEntityType object at 0x7f9e686f3fd0>>

A frame whose labels are to be predicted.

label_column : unicode

Column containing the actual label for each observation.

observation_columns : list (default=None)

Column(s) containing the observations whose labels are to be predicted and tested. Default is to test over the columns the LIBSVM model was trained on.

Headers

Authorization: test_api_key_1
Content-type: application/json

Description

Predict the labels for a test frame and run classification metrics on predicted and target labels.

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

Object with binary classification metrics. The data returned is composed of multiple components:

double : accuracy

The degree of correctness of the test frame labels.

table : confusion_matrix

A specific table layout that allows visualization of the performance of the

test. | double : f_measure | A measure of a test’s accuracy. It considers both the precision and the recall of the test to compute the score. | double : precision | The degree to which the correctness of the label is expressed. | double : recall | The fraction of relevant instances that are retrieved.