Package weka.classifiers.evaluation

Interface Summary

Interface	Description
InformationRetrievalEvaluationMetric	An interface for information retrieval evaluation metrics to implement.
InformationTheoreticEvaluationMetric	Primarily a marker interface for information theoretic evaluation metrics to implement.
IntervalBasedEvaluationMetric	Primarily a marker interface for interval-based evaluation metrics to implement.
Prediction	Encapsulates a single evaluatable prediction: the predicted value plus the actual class value.
StandardEvaluationMetric	Primarily a marker interface for a "standard" evaluation metric - i.e.
ThresholdProducingMetric	Some evaluation measures may optimize thresholds on the class probabilities.

Class Summary

Class	Description
AbstractEvaluationMetric	Abstract base class for pluggable classification/regression evaluation metrics.
AggregateableEvaluation	Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.
ConfusionMatrix	Cells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination.
CostCurve	Generates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes.
Evaluation	Class for evaluating machine learning models.
EvaluationMetricHelper	Helper routines for extracting metric values from built-in and plugin evaluation metrics.
EvaluationUtils	Contains utility functions for generating lists of predictions in various manners.
MarginCurve	Generates points illustrating the prediction margin.
NominalPrediction	Encapsulates an evaluatable nominal prediction: the predicted probability distribution plus the actual class value.
NumericPrediction	Encapsulates an evaluatable numeric prediction: the predicted class value plus the actual class value.
RegressionAnalysis	Analyzes linear regression model by using the Student's t-test on each coefficient.
ThresholdCurve	Generates points illustrating prediction tradeoffs that can be obtained by varying the threshold value between classes.
TwoClassStats	Encapsulates performance functions for two-class problems.

Exception Summary

Exception	Description