de.lmu.ifi.dbs.elki.evaluation.scores

Interface ScoreEvaluation

All Known Implementing Classes:

AbstractScoreEvaluation, AveragePrecisionEvaluation, MaximumF1Evaluation, PrecisionAtKEvaluation, ROCEvaluation

public interface ScoreEvaluation

Compute ranking/scoring based evaluation measures.

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Interface and Description
static interface	ScoreEvaluation.Predicate<T> Predicate to test whether an object is a true positive or false positive.
static interface	ScoreEvaluation.ScoreIter Iterator for comparing scores.

Method Summary

Methods

Modifier and Type	Method and Description
double	evaluate(Cluster<?> clus, DoubleDBIDList nei) Evaluate given a cluster (of positive elements) and a scoring list.
double	evaluate(DBIDs ids, DoubleDBIDList nei) Evaluate given a list of positives and a scoring.
double	evaluate(DBIDs ids, OutlierResult outlier) Evaluate given a set of positives and a scoring.
<I extends ScoreEvaluation.ScoreIter> double	evaluate(ScoreEvaluation.Predicate<? super I> predicate, I iter) Evaluate a given predicate and iterator.
double	expected(int pos, int all) Expected score for a random result.

Method Detail

evaluate

<I extends ScoreEvaluation.ScoreIter> double evaluate(ScoreEvaluation.Predicate<? super I> predicate,
                                                    I iter)

Evaluate a given predicate and iterator.

Type Parameters:

I - Iterator type

Parameters:

predicate - Predicate (for positives)

iter - Iterator

Returns:

Score

evaluate

double evaluate(Cluster<?> clus,
              DoubleDBIDList nei)

Evaluate given a cluster (of positive elements) and a scoring list.

Parameters:

clus - Cluster object

nei - Query result

Returns:

Score

evaluate

double evaluate(DBIDs ids,
              DoubleDBIDList nei)

Evaluate given a list of positives and a scoring.

Parameters:

ids - Positive IDs, usually a set.

nei - Query Result

Returns:

Score

evaluate

double evaluate(DBIDs ids,
              OutlierResult outlier)

Evaluate given a set of positives and a scoring.

Parameters:

ids - Positive IDs, usually a set.

outlier - Outlier detection result

Returns:

Score

expected

double expected(int pos,
              int all)

Expected score for a random result.

Parameters:

pos - Number of positive elements

all - Total number of elements

Returns:

Expected score