com.ibm.watson.developer_cloud.personality_insights.v2.model

Class Trait

java.lang.Object

com.ibm.watson.developer_cloud.service.model.GenericModel

com.ibm.watson.developer_cloud.personality_insights.v2.model.Trait

public class Trait
extends GenericModel

The personality trait/model POJO class.

Constructor Summary

Constructors

Constructor and Description
Trait()

Method Summary

Modifier and Type	Method and Description
String	getCategory() Gets the personality model category.
List<Trait>	getChildren() Gets the characteristic children.
String	getId() Gets id of the characteristic, globally unique.
String	getName() Gets the user-displayable name of the characteristic.
Double	getPercentage() Gets the normalized value of the characteristic, from 0-1.
Double	getRawSamplingError() Gets the raw sampling error.
Double	getRawScore() Gets the raw score.
Double	getSamplingError() Indicates the sampling error of the percentage, based on the number of words in the input.
void	setCategory(String category) Sets personality model category.
void	setChildren(List<Trait> children) Sets the characteristic children.
void	setId(String id) Sets the id of the characteristic, globally unique.
void	setName(String name) Sets the user-displayable name of the characteristic.
void	setPercentage(Double percentage) Sets the normalized value of the characteristic, from 0-1.
void	setRawSamplingError(Double rawSamplingError) Sets the raw sampling error.
void	setRawScore(Double rawScore) Sets the raw score.
void	setSamplingError(Double samplingError) Sets the sampling error of the percentage based on the number of words in the input.

Methods inherited from class com.ibm.watson.developer_cloud.service.model.GenericModel

equals, hashCode, toString

Methods inherited from class java.lang.Object

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

Constructor Detail

Trait

public Trait()

Method Detail

getCategory

public String getCategory()

Gets the personality model category. e.g: "values", "needs" or "personality"

Returns:

the category

getChildren

public List<Trait> getChildren()

Gets the characteristic children.

Returns:

the children

getId

public String getId()

Gets id of the characteristic, globally unique.

Returns:

the characteristic identifier

getName

public String getName()

Gets the user-displayable name of the characteristic.

Returns:

the name

getPercentage

public Double getPercentage()

Gets the normalized value of the characteristic, from 0-1. For example, if the percentage for Openness is 0.25, you scored in the 25th percentile. You are more open than 24% of the population and less open than 74% of the population.,

Returns:

the percentage

getRawSamplingError

public Double getRawSamplingError()

Gets the raw sampling error.

Returns:

the raw sampling error

getRawScore

public Double getRawScore()

Gets the raw score.

Returns:

the raw score

getSamplingError

public Double getSamplingError()

Indicates the sampling error of the percentage, based on the number of words in the input. The number defines a 95% confidence interval around the percentage. For example, the sampling error is 4% and percentage is 61%. It is 95% likely that the actual percentage value is between 57% and 65% if more words are given.

Returns:

the sampling error

setCategory

public void setCategory(String category)

Sets personality model category. e.g: "values", "needs" or "personality"

Parameters:

category - the new category

setChildren

public void setChildren(List<Trait> children)

Sets the characteristic children.

Parameters:

children - the new children

setId

public void setId(String id)

Sets the id of the characteristic, globally unique.

Parameters:

id - the characteristic identifier

setName

public void setName(String name)

Sets the user-displayable name of the characteristic.

Parameters:

name - the new name

setPercentage

public void setPercentage(Double percentage)

Sets the normalized value of the characteristic, from 0-1.

Parameters:

percentage - the new percentage value from 0-1

setRawSamplingError

public void setRawSamplingError(Double rawSamplingError)

Sets the raw sampling error.

Parameters:

rawSamplingError - the new raw sampling error

setRawScore

public void setRawScore(Double rawScore)

Sets the raw score.

Parameters:

rawScore - the new raw score

setSamplingError

public void setSamplingError(Double samplingError)

Sets the sampling error of the percentage based on the number of words in the input.

Parameters:

samplingError - error the new sampling error