| 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 | 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 | Description |
|---|