| Interface | Description |
|---|---|
| Measurable |
Defines the interface, a class for which heuristic values can be calculated according to
different
Heuristics, must implement. |
| TieBreaker<T extends Measurable> |
Defines the interface, a tie breaker, that allows to decide which one of two
Measurables
that evaluate to the same heuristic value is considered to be better, must implement. |
| Class | Description |
|---|---|
| Accuracy |
A heuristic that calculates the accuracy of predictions based on a
ConfusionMatrix. |
| ConfusionMatrix |
A 2-dimensional confusion matrix that stores how many true positives (TP), false positives (FP),
true negatives (TN), and false negatives (FN) have been predicted by a classifier.
|
| FMeasure |
A heuristic that calculates the F-Measure of predictions based on a
ConfusionMatrix. |
| HammingLoss |
A heuristic that calculates the heuristic value of predictions according to the Hamming Loss
based on a
ConfusionMatrix. |
| Heuristic |
Defines the interface, a heuristic that calculates a heuristic value based on a
ConfusionMatrix, must implement. |
| Heuristic.Comparator<T extends Measurable> |
A comparator that allows to compare
Measurables based on their heuristic values
according to a certain Heuristic. |
| JaccardIndex |
A heuristic that calculates the heuristic value of predictions according to the Jaccard index
based on a
ConfusionMatrix. |
| Laplace |
A heuristic that calculates the heuristic value of predictions according to the Laplace metric
based on a
ConfusionMatrix. |
| MEstimate |
A heuristic that calculates the m-estimate of predictions based on a
ConfusionMatrix. |
| Precision |
A heuristic that calculates the precision of predictions based on a
ConfusionMatrix. |
| Recall |
A heuristic that calculates the recall (also known as true positive rate) of predictions based on
a
ConfusionMatrix. |
| Enum | Description |
|---|---|
| ConfusionMatrix.Element |
Contains all types of elements of a
ConfusionMatrix. |