hex.genmodel.easy

Class EasyPredictModelWrapper

java.lang.Object

hex.genmodel.easy.EasyPredictModelWrapper

public class EasyPredictModelWrapper
extends java.lang.Object

An easy-to-use prediction wrapper for generated models. Note that for any given model, you must use the exact one correct predict method below based on the model category.

See the top-of-tree master version of this file here on github.

Constructor Summary

Constructors

Constructor and Description
EasyPredictModelWrapper(GenModel model) Create a wrapper for a generated model.

Method Summary

Methods

Modifier and Type	Method and Description
java.lang.String	getHeader() Some autoencoder thing, I'm not sure what this does.
ModelCategory	getModelCategory() Get the category (type) of model.
java.lang.String[]	getResponseDomainValues() Get the array of levels for the response column.
AutoEncoderModelPrediction	predictAutoEncoder(RowData data) Make a prediction on a new data point using an AutoEncoder model.
BinomialModelPrediction	predictBinomial(RowData data) Make a prediction on a new data point using a Binomial model.
ClusteringModelPrediction	predictClustering(RowData data) Make a prediction on a new data point using a Clustering model.
MultinomialModelPrediction	predictMultinomial(RowData data) Make a prediction on a new data point using a Multinomial model.
RegressionModelPrediction	predictRegression(RowData data) Make a prediction on a new data point using a Regression model.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

EasyPredictModelWrapper

public EasyPredictModelWrapper(GenModel model)

Create a wrapper for a generated model.

Parameters:

model - The generated model

Method Detail

predictAutoEncoder

public AutoEncoderModelPrediction predictAutoEncoder(RowData data)
                                              throws AbstractPredictException

Make a prediction on a new data point using an AutoEncoder model.

Parameters:

data - A new data point.

Returns:

The prediction.

Throws:

AbstractPredictException

predictBinomial

public BinomialModelPrediction predictBinomial(RowData data)
                                        throws AbstractPredictException

Make a prediction on a new data point using a Binomial model.

Parameters:

data - A new data point.

Returns:

The prediction.

Throws:

AbstractPredictException

predictMultinomial

public MultinomialModelPrediction predictMultinomial(RowData data)
                                              throws AbstractPredictException

Make a prediction on a new data point using a Multinomial model.

Parameters:

data - A new data point.

Returns:

The prediction.

Throws:

AbstractPredictException

predictClustering

public ClusteringModelPrediction predictClustering(RowData data)
                                            throws AbstractPredictException

Make a prediction on a new data point using a Clustering model.

Parameters:

data - A new data point.

Returns:

The prediction.

Throws:

AbstractPredictException

predictRegression

public RegressionModelPrediction predictRegression(RowData data)
                                            throws AbstractPredictException

Make a prediction on a new data point using a Regression model.

Parameters:

data - A new data point.

Returns:

The prediction.

Throws:

AbstractPredictException

getModelCategory

public ModelCategory getModelCategory()

Get the category (type) of model.

Returns:

The category.

getResponseDomainValues

public java.lang.String[] getResponseDomainValues()

Get the array of levels for the response column. "Domain" just means list of level names for a categorical (aka factor, enum) column. If the response column is numerical and not categorical, this will return null.

Returns:

The array.

getHeader

public java.lang.String getHeader()

Some autoencoder thing, I'm not sure what this does.

Returns:

CSV header for autoencoder.