All Packages Class Hierarchy This Package Previous Next Index WEKA's home
Class weka.classifiers.evaluation.NominalPrediction
java.lang.Object
|
+----weka.classifiers.evaluation.NominalPrediction
- public class NominalPrediction
- extends java.lang.Object
- implements Prediction, java.io.Serializable
Encapsulates an evaluatable nominal prediction: the predicted probability
distribution plus the actual class value.
- Version:
- $Revision: 1.8 $
- Author:
- Len Trigg (len@intelligenesis.net)
NominalPrediction(double, double[])
- Creates the NominalPrediction object with a default weight of 1.0.
NominalPrediction(double, double[], double)
- Creates the NominalPrediction object.
actual()
- Gets the actual class value.
distribution()
- Gets the predicted probabilities
makeDistribution(double, int)
- Convert a single prediction into a probability distribution
with all zero probabilities except the predicted value which
has probability 1.0.
makeUniformDistribution(int)
- Creates a uniform probability distribution -- where each of the
possible classes is assigned equal probability.
margin()
- Calculates the prediction margin.
predicted()
- Gets the predicted class value.
toString()
- Gets a human readable representation of this prediction.
weight()
- Gets the weight assigned to this prediction.
NominalPrediction
public NominalPrediction(double actual,
double distribution[])
Creates the NominalPrediction object with a default weight of 1.0.
- Parameters:
actual
- the actual value, or MISSING_VALUE.
distribution
- the predicted probability distribution. Use
NominalPrediction.makeDistribution() if you only know the predicted value.
NominalPrediction
public NominalPrediction(double actual,
double distribution[],
double weight)
Creates the NominalPrediction object.
- Parameters:
actual
- the actual value, or MISSING_VALUE.
distribution
- the predicted probability distribution. Use
NominalPrediction.makeDistribution() if you only know the predicted value.
weight
- the weight assigned to the prediction.
distribution
public double[] distribution()
Gets the predicted probabilities
actual
public double actual()
Gets the actual class value.
- Returns:
- the actual class value, or MISSING_VALUE if no
prediction was made.
predicted
public double predicted()
Gets the predicted class value.
- Returns:
- the predicted class value, or MISSING_VALUE if no
prediction was made.
weight
public double weight()
Gets the weight assigned to this prediction. This is typically the weight
of the test instance the prediction was made for.
- Returns:
- the weight assigned to this prediction.
margin
public double margin()
Calculates the prediction margin. This is defined as the difference
between the probability predicted for the actual class and the highest
predicted probability of the other classes.
- Returns:
- the margin for this prediction, or
MISSING_VALUE if either the actual or predicted value
is missing.
makeDistribution
public static double[] makeDistribution(double predictedClass,
int numClasses)
Convert a single prediction into a probability distribution
with all zero probabilities except the predicted value which
has probability 1.0. If no prediction was made, all probabilities
are zero.
- Parameters:
predictedClass
- the index of the predicted class, or
MISSING_VALUE if no prediction was made.
numClasses
- the number of possible classes for this nominal
prediction.
- Returns:
- the probability distribution.
makeUniformDistribution
public static double[] makeUniformDistribution(int numClasses)
Creates a uniform probability distribution -- where each of the
possible classes is assigned equal probability.
- Parameters:
numClasses
- the number of possible classes for this nominal
prediction.
- Returns:
- the probability distribution.
toString
public java.lang.String toString()
Gets a human readable representation of this prediction.
- Returns:
- a human readable representation of this prediction.
- Overrides:
- toString in class java.lang.Object
All Packages Class Hierarchy This Package Previous Next Index WEKA's home