com.google.api.services.language.v2.model

Class XPSTablesModelColumnInfo

java.lang.Object

java.util.AbstractMap<String,Object>

com.google.api.client.util.GenericData

com.google.api.client.json.GenericJson

com.google.api.services.language.v2.model.XPSTablesModelColumnInfo

All Implemented Interfaces:

Cloneable, Map<String,Object>

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

An information specific to given column and Tables Model, in context of the Model and the predictions created by it.

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 Cloud Natural Language 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/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

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

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

Map.Entry<K,V>

Constructor Summary

Constructors

Constructor and Description
XPSTablesModelColumnInfo()

Method Summary

Modifier and Type	Method and Description
XPSTablesModelColumnInfo	clone()
Integer	getColumnId() The ID of the column.
Float	getFeatureImportance() When given as part of a Model: Measurement of how much model predictions correctness on the TEST data depend on values in this column.
XPSTablesModelColumnInfo	set(String fieldName, Object value)
XPSTablesModelColumnInfo	setColumnId(Integer columnId) The ID of the column.
XPSTablesModelColumnInfo	setFeatureImportance(Float featureImportance) When given as part of a Model: Measurement of how much model predictions correctness on the TEST data depend on values in this column.

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, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap

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

Methods inherited from class java.lang.Object

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

Methods inherited from interface java.util.Map

compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

Constructor Detail

XPSTablesModelColumnInfo

public XPSTablesModelColumnInfo()

Method Detail

getColumnId

public Integer getColumnId()

The ID of the column.

Returns:

value or null for none

setColumnId

public XPSTablesModelColumnInfo setColumnId(Integer columnId)

The ID of the column.

Parameters:

columnId - columnId or null for none

getFeatureImportance

public Float getFeatureImportance()

When given as part of a Model: Measurement of how much model predictions correctness on the TEST data depend on values in this column. A value between 0 and 1, higher means higher influence. These values are normalized - for all input feature columns of a given model they add to 1. When given back by Predict or Batch Predict: Measurement of how impactful for the prediction returned for the given row the value in this column was. Specifically, the feature importance specifies the marginal contribution that the feature made to the prediction score compared to the baseline score. These values are computed using the Sampled Shapley method.

Returns:

value or null for none

setFeatureImportance

public XPSTablesModelColumnInfo setFeatureImportance(Float featureImportance)

When given as part of a Model: Measurement of how much model predictions correctness on the TEST data depend on values in this column. A value between 0 and 1, higher means higher influence. These values are normalized - for all input feature columns of a given model they add to 1. When given back by Predict or Batch Predict: Measurement of how impactful for the prediction returned for the given row the value in this column was. Specifically, the feature importance specifies the marginal contribution that the feature made to the prediction score compared to the baseline score. These values are computed using the Sampled Shapley method.

Parameters:

featureImportance - featureImportance or null for none

set

public XPSTablesModelColumnInfo set(String fieldName,
                                    Object value)

Overrides:

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

clone

public XPSTablesModelColumnInfo clone()

Overrides:

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