com.google.api.services.prediction.model

Class Insert

java.lang.Object

java.util.AbstractMap<java.lang.String,java.lang.Object>

com.google.api.client.util.GenericData

com.google.api.client.json.GenericJson

com.google.api.services.prediction.model.Insert

All Implemented Interfaces:

java.lang.Cloneable, java.util.Map<java.lang.String,java.lang.Object>

public final class Insert
extends com.google.api.client.json.GenericJson

Model definition for Insert.

This is the Java data model class that specifies how to parse/serialize into the JSON that is transmitted over HTTP when working with the Prediction API. For a detailed explanation see: https://developers.google.com/api-client-library/java/google-http-java-client/json

Author:

Google, Inc.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Insert.TrainingInstances Model definition for InsertTrainingInstances.

Nested classes/interfaces inherited from class com.google.api.client.util.GenericData

com.google.api.client.util.GenericData.Flags

Nested classes/interfaces inherited from class java.util.AbstractMap

java.util.AbstractMap.SimpleEntry<K,V>, java.util.AbstractMap.SimpleImmutableEntry<K,V>

Nested classes/interfaces inherited from interface java.util.Map

java.util.Map.Entry<K,V>

Constructor Summary

Constructors

Constructor and Description
Insert()

Method Summary

Methods

Modifier and Type	Method and Description
Insert	clone()
java.lang.String	getId() The unique name for the predictive model.
java.lang.String	getModelType() Type of predictive model (classification or regression).
java.lang.String	getSourceModel() The Id of the model to be copied over.
java.lang.String	getStorageDataLocation() Google storage location of the training data file.
java.lang.String	getStoragePMMLLocation() Google storage location of the preprocessing pmml file.
java.lang.String	getStoragePMMLModelLocation() Google storage location of the pmml model file.
java.util.List<Insert.TrainingInstances>	getTrainingInstances() Instances to train model on.
java.util.List<java.util.Map<java.lang.String,java.lang.Double>>	getUtility() A class weighting function, which allows the importance weights for class labels to be specified (Categorical models only).
Insert	set(java.lang.String fieldName, java.lang.Object value)
Insert	setId(java.lang.String id) The unique name for the predictive model.
Insert	setModelType(java.lang.String modelType) Type of predictive model (classification or regression).
Insert	setSourceModel(java.lang.String sourceModel) The Id of the model to be copied over.
Insert	setStorageDataLocation(java.lang.String storageDataLocation) Google storage location of the training data file.
Insert	setStoragePMMLLocation(java.lang.String storagePMMLLocation) Google storage location of the preprocessing pmml file.
Insert	setStoragePMMLModelLocation(java.lang.String storagePMMLModelLocation) Google storage location of the pmml model file.
Insert	setTrainingInstances(java.util.List<Insert.TrainingInstances> trainingInstances) Instances to train model on.
Insert	setUtility(java.util.List<java.util.Map<java.lang.String,java.lang.Double>> utility) A class weighting function, which allows the importance weights for class labels to be specified (Categorical models only).

Methods inherited from class com.google.api.client.json.GenericJson

getFactory, setFactory, toPrettyString, toString

Methods inherited from class com.google.api.client.util.GenericData

entrySet, get, getClassInfo, getUnknownKeys, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap

clear, containsKey, containsValue, equals, hashCode, isEmpty, keySet, size, values

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

Insert

public Insert()

Method Detail

getId

public java.lang.String getId()

The unique name for the predictive model.

Returns:

value or null for none

setId

public Insert setId(java.lang.String id)

The unique name for the predictive model.

Parameters:

id - id or null for none

getModelType

public java.lang.String getModelType()

Type of predictive model (classification or regression).

Returns:

value or null for none

setModelType

public Insert setModelType(java.lang.String modelType)

Type of predictive model (classification or regression).

Parameters:

modelType - modelType or null for none

getSourceModel

public java.lang.String getSourceModel()

The Id of the model to be copied over.

Returns:

value or null for none

setSourceModel

public Insert setSourceModel(java.lang.String sourceModel)

The Id of the model to be copied over.

Parameters:

sourceModel - sourceModel or null for none

getStorageDataLocation

public java.lang.String getStorageDataLocation()

Google storage location of the training data file.

Returns:

value or null for none

setStorageDataLocation

public Insert setStorageDataLocation(java.lang.String storageDataLocation)

Google storage location of the training data file.

Parameters:

storageDataLocation - storageDataLocation or null for none

getStoragePMMLLocation

public java.lang.String getStoragePMMLLocation()

Google storage location of the preprocessing pmml file.

Returns:

value or null for none

setStoragePMMLLocation

public Insert setStoragePMMLLocation(java.lang.String storagePMMLLocation)

Google storage location of the preprocessing pmml file.

Parameters:

storagePMMLLocation - storagePMMLLocation or null for none

getStoragePMMLModelLocation

public java.lang.String getStoragePMMLModelLocation()

Google storage location of the pmml model file.

Returns:

value or null for none

setStoragePMMLModelLocation

public Insert setStoragePMMLModelLocation(java.lang.String storagePMMLModelLocation)

Google storage location of the pmml model file.

Parameters:

storagePMMLModelLocation - storagePMMLModelLocation or null for none

getTrainingInstances

public java.util.List<Insert.TrainingInstances> getTrainingInstances()

Instances to train model on.

Returns:

value or null for none

setTrainingInstances

public Insert setTrainingInstances(java.util.List<Insert.TrainingInstances> trainingInstances)

Instances to train model on.

Parameters:

trainingInstances - trainingInstances or null for none

getUtility

public java.util.List<java.util.Map<java.lang.String,java.lang.Double>> getUtility()

A class weighting function, which allows the importance weights for class labels to be specified (Categorical models only).

Returns:

value or null for none

setUtility

public Insert setUtility(java.util.List<java.util.Map<java.lang.String,java.lang.Double>> utility)

A class weighting function, which allows the importance weights for class labels to be specified (Categorical models only).

Parameters:

utility - utility or null for none

set

public Insert set(java.lang.String fieldName,
         java.lang.Object value)

Overrides:

set in class com.google.api.client.json.GenericJson

clone

public Insert clone()

Overrides:

clone in class com.google.api.client.json.GenericJson