GpInsert: GpInsert

Description Usage Arguments Value References

View source: R/GpInsert.R

Description

Train a Prediction API model.

Usage

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  GpInsert(model_id, project, oauth, source_model = NULL,
    storage_location = NULL, storage_pmml_location = NULL,
    storage_pmml_model_location = NULL, model_type = NULL,
    training_instances = NULL, utility = NULL)

Arguments

model_id

The unique name for the predictive model.

project

The project associated with the model.

oauth

The httr OAuth2.0 token reference class object to use for authentication.

source_model

optional The Id of the model to be copied over.

storage_location

optional Google storage location of the training data file.

storage_pmml_location

optional Google storage location of the preprocessing pmml file.

storage_pmml_model_location

optional Google storage location of the pmml model file.

model_type

optional Type of predictive model (CLASSIFICATION or REGRESSION)

training_instances

optional List of outputs and csvInstances to train model on. An output is a string with the generic output value - could be regression or class label. A csvInstance is the input features for that instance.

utility

optional A class weighting function, which allows the importance weights for class labels to be specified (Categorical models only). A list of numeric keys (double)

Value

JSON response from the Google Prediction API converted into an R List.

References

Trainedmodels: insert https://developers.google.com/prediction/docs/reference/v1.6/trainedmodels/insert


jdeboer/gprediction documentation built on May 17, 2017, 8:14 p.m.