Class Predictions
- java.lang.Object
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- adams.core.logging.LoggingObject
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- adams.core.logging.CustomLoggingLevelObject
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- adams.core.option.AbstractOptionHandler
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- adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput<adams.data.spreadsheet.SpreadSheet>
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- adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions
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- All Implemented Interfaces:
adams.core.Destroyable
,adams.core.GlobalInfoSupporter
,adams.core.logging.LoggingLevelHandler
,adams.core.logging.LoggingSupporter
,adams.core.option.OptionHandler
,adams.core.QuickInfoSupporter
,adams.core.SizeOfHandler
,Serializable
public class Predictions extends AbstractWekaRepeatedCrossValidationOutput<adams.data.spreadsheet.SpreadSheet>
Generates statistics for predictions from repeated cross-validation runs.- Author:
- FracPete (fracpete at waikato dot ac dot nz)
- See Also:
- Serialized Form
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Field Summary
Fields Modifier and Type Field Description protected LowerStatistic
m_Lower
the lower value to compute.protected CenterStatistic
m_Statistic
the statistic to generate.protected UpperStatistic
m_Upper
the upper value to compute.
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Constructor Summary
Constructors Constructor Description Predictions()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description void
defineOptions()
Adds options to the internal list of options.protected adams.data.spreadsheet.SpreadSheet
doGenerateOutput(WekaEvaluationContainer[] conts)
Generates the data.Class
generates()
Returns the class that it generates.LowerStatistic
getLower()
Returns the lower value to output.String
getQuickInfo()
Returns a quick info about the object, which can be displayed in the GUI.CenterStatistic
getStatistic()
Returns the statistic to output.UpperStatistic
getUpper()
Returns the upper value to output.String
globalInfo()
Returns a string describing the object.String
handles(WekaEvaluationContainer[] conts)
Checks whether the cross-validation results can be processed.String
lowerTipText()
Returns the tip text for this property.void
setLower(LowerStatistic value)
Sets the lower value to output.void
setStatistic(CenterStatistic value)
Sets the statistic to output.void
setUpper(UpperStatistic value)
Sets the upper value to output.String
statisticTipText()
Returns the tip text for this property.String
upperTipText()
Returns the tip text for this property.-
Methods inherited from class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput
generateOutput
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Methods inherited from class adams.core.option.AbstractOptionHandler
cleanUpOptions, destroy, finishInit, getDefaultLoggingLevel, getOptionManager, initialize, loggingLevelTipText, newOptionManager, reset, setLoggingLevel, toCommandLine, toString
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Methods inherited from class adams.core.logging.LoggingObject
configureLogger, getLogger, getLoggingLevel, initializeLogging, isLoggingEnabled, sizeOf
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Field Detail
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m_Statistic
protected CenterStatistic m_Statistic
the statistic to generate.
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m_Lower
protected LowerStatistic m_Lower
the lower value to compute.
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m_Upper
protected UpperStatistic m_Upper
the upper value to compute.
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Method Detail
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globalInfo
public String globalInfo()
Returns a string describing the object.- Specified by:
globalInfo
in interfaceadams.core.GlobalInfoSupporter
- Specified by:
globalInfo
in classadams.core.option.AbstractOptionHandler
- Returns:
- a description suitable for displaying in the gui
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defineOptions
public void defineOptions()
Adds options to the internal list of options.- Specified by:
defineOptions
in interfaceadams.core.option.OptionHandler
- Overrides:
defineOptions
in classadams.core.option.AbstractOptionHandler
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setStatistic
public void setStatistic(CenterStatistic value)
Sets the statistic to output.- Parameters:
value
- the statistic
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getStatistic
public CenterStatistic getStatistic()
Returns the statistic to output.- Returns:
- the statistic
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statisticTipText
public String statisticTipText()
Returns the tip text for this property.- Returns:
- tip text for this property suitable for displaying in the GUI or for listing the options.
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setLower
public void setLower(LowerStatistic value)
Sets the lower value to output.- Parameters:
value
- the lower value
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getLower
public LowerStatistic getLower()
Returns the lower value to output.- Returns:
- the lower value
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lowerTipText
public String lowerTipText()
Returns the tip text for this property.- Returns:
- tip text for this property suitable for displaying in the GUI or for listing the options.
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setUpper
public void setUpper(UpperStatistic value)
Sets the upper value to output.- Parameters:
value
- the upper value
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getUpper
public UpperStatistic getUpper()
Returns the upper value to output.- Returns:
- the upper value
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upperTipText
public String upperTipText()
Returns the tip text for this property.- Returns:
- tip text for this property suitable for displaying in the GUI or for listing the options.
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generates
public Class generates()
Returns the class that it generates.- Specified by:
generates
in classAbstractWekaRepeatedCrossValidationOutput<adams.data.spreadsheet.SpreadSheet>
- Returns:
- the class
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getQuickInfo
public String getQuickInfo()
Returns a quick info about the object, which can be displayed in the GUI.- Specified by:
getQuickInfo
in interfaceadams.core.QuickInfoSupporter
- Overrides:
getQuickInfo
in classAbstractWekaRepeatedCrossValidationOutput<adams.data.spreadsheet.SpreadSheet>
- Returns:
- null if no info available, otherwise short string
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handles
public String handles(WekaEvaluationContainer[] conts)
Checks whether the cross-validation results can be processed.- Specified by:
handles
in classAbstractWekaRepeatedCrossValidationOutput<adams.data.spreadsheet.SpreadSheet>
- Parameters:
conts
- the containers to check- Returns:
- null if the data can be processed, otherwise an error message
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doGenerateOutput
protected adams.data.spreadsheet.SpreadSheet doGenerateOutput(WekaEvaluationContainer[] conts)
Generates the data.- Specified by:
doGenerateOutput
in classAbstractWekaRepeatedCrossValidationOutput<adams.data.spreadsheet.SpreadSheet>
- Parameters:
conts
- the containers to process- Returns:
- the generated data
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