# 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
  --- | ---