com.ibm.watson.personality_insights.v3.model

Class ConsumptionPreferences

java.lang.Object

com.ibm.cloud.sdk.core.service.model.GenericModel

com.ibm.watson.personality_insights.v3.model.ConsumptionPreferences

All Implemented Interfaces:

com.ibm.cloud.sdk.core.service.model.ObjectModel

public class ConsumptionPreferences
extends com.ibm.cloud.sdk.core.service.model.GenericModel

A consumption preference that the service inferred from the input content.

Field Summary

Fields

Modifier and Type	Field and Description
protected java.lang.String	consumptionPreferenceId
protected java.lang.String	name
protected java.lang.Double	score

Constructor Summary

Constructors

Constructor and Description
ConsumptionPreferences()

Method Summary

Modifier and Type	Method and Description
java.lang.String	getConsumptionPreferenceId() Gets the consumptionPreferenceId.
java.lang.String	getName() Gets the name.
java.lang.Double	getScore() Gets the score.

Methods inherited from class com.ibm.cloud.sdk.core.service.model.GenericModel

equals, hashCode, toString

Methods inherited from class java.lang.Object

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

Field Detail

consumptionPreferenceId

@SerializedName(value="consumption_preference_id")
protected java.lang.String consumptionPreferenceId

name

protected java.lang.String name

score

protected java.lang.Double score

Constructor Detail

ConsumptionPreferences

public ConsumptionPreferences()

Method Detail

getConsumptionPreferenceId

public java.lang.String getConsumptionPreferenceId()

Gets the consumptionPreferenceId.

The unique, non-localized identifier of the consumption preference to which the results pertain. IDs have the form `consumption_preferences_{preference}`.

Returns:

the consumptionPreferenceId

getName

public java.lang.String getName()

Gets the name.

The user-visible, localized name of the consumption preference.

Returns:

the name

getScore

public java.lang.Double getScore()

Gets the score.

The score for the consumption preference: * `0.0`: Unlikely * `0.5`: Neutral * `1.0`: Likely

The scores for some preferences are binary and do not allow a neutral value. The score is an indication of preference based on the results inferred from the input text, not a normalized percentile.

Returns:

the score