Commands model:random_forest_regressor/new¶
Create a ‘new’ instance of a Random Forest Regressor model.
POST /v1/commands/¶
GET /v1/commands/:id¶
Request¶
Route
POST /v1/commands/
Body
| name: | model:random_forest_regressor/new |
|---|---|
| arguments: | dummy_model_ref : Model
name : unicode (default=None)
|
Headers
Authorization: test_api_key_1
Content-type: application/json
Description
Random Forest [1] is a supervised ensemble learning algorithm used to perform regression. A Random Forest Regressor model is initialized, trained on columns of a frame, and used to predict the value of each observation in the frame. This model runs the MLLib implementation of Random Forest [2]. During training, the decision trees are trained in parallel. During prediction, the average over-all tree’s predicted value is the predicted value of the random forest.
footnotes
| [1] | https://en.wikipedia.org/wiki/Random_forest |
| [2] | https://spark.apache.org/docs/1.5.0/mllib-ensembles.html#random-forests |
Response¶
Status
200 OK
Body
Returns information about the command. See the Response Body for Get Command here below. It is the same.