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Class weka.classifiers.evaluation.NominalPrediction
java.lang.Object
|
+----weka.classifiers.evaluation.NominalPrediction
- public class NominalPrediction
- extends Object
- implements Prediction, Serializable
Encapsulates an evaluatable nominal prediction: the predicted probability
distribution plus the actual class value.
- 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 String toString()
- Gets a human readable representation of this prediction.
- Returns:
- a human readable representation of this prediction.
- Overrides:
- toString in class Object
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