Package | Description |
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de.unibi.techfak.scie.classifiers |
Modifier and Type | Method and Description |
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static ClassifierEvaluation |
TrainingUtils.crossValidation(ArrayList<LabeledDataPoint> trainingData,
Classifier classifier,
int folds,
int times,
Comparator<ClassifierEvaluation> comparator,
boolean verbose)
Trains the given classifier using crossvalidation and taking the result
with the best evaluation result according to the given comparator.
|
static <C extends Classifier> |
TrainingUtils.crossValidationSweep(ArrayList<LabeledDataPoint> trainingData,
C classifier,
int folds,
int times,
TrainingUtils.ParameterSweep<C> sweep,
Comparator<ClassifierEvaluation> comparator,
boolean verbose)
Does the cross validation but does the given parameter sweep in an outer
loop.
|
static <C extends Classifier> |
TrainingUtils.simpleParameterSweep(ArrayList<LabeledDataPoint> trainingData,
C classifier,
double testRatio,
TrainingUtils.ParameterSweep<C> sweep,
int times,
Comparator<ClassifierEvaluation> comparator,
boolean verbose)
Does the simple training but does the given parameter sweep in an outer
loop.
|
static ClassifierEvaluation |
TrainingUtils.simpleTraining(ArrayList<LabeledDataPoint> trainingData,
Classifier classifier,
double testRatio,
int times,
Comparator<ClassifierEvaluation> comparator,
boolean verbose)
Chooses randomly testRatio datapoints for testing, trains the classifier
with the rest and reports precision, recall and accuracy for the test
set.
|
Modifier and Type | Method and Description |
---|---|
static ClassifierEvaluation |
TrainingUtils.crossValidation(ArrayList<LabeledDataPoint> trainingData,
Classifier classifier,
int folds,
int times,
Comparator<ClassifierEvaluation> comparator,
boolean verbose)
Trains the given classifier using crossvalidation and taking the result
with the best evaluation result according to the given comparator.
|
static <C extends Classifier> |
TrainingUtils.crossValidationSweep(ArrayList<LabeledDataPoint> trainingData,
C classifier,
int folds,
int times,
TrainingUtils.ParameterSweep<C> sweep,
Comparator<ClassifierEvaluation> comparator,
boolean verbose)
Does the cross validation but does the given parameter sweep in an outer
loop.
|
static <C extends Classifier> |
TrainingUtils.simpleParameterSweep(ArrayList<LabeledDataPoint> trainingData,
C classifier,
double testRatio,
TrainingUtils.ParameterSweep<C> sweep,
int times,
Comparator<ClassifierEvaluation> comparator,
boolean verbose)
Does the simple training but does the given parameter sweep in an outer
loop.
|
static ClassifierEvaluation |
TrainingUtils.simpleTraining(ArrayList<LabeledDataPoint> trainingData,
Classifier classifier,
double testRatio,
int times,
Comparator<ClassifierEvaluation> comparator,
boolean verbose)
Chooses randomly testRatio datapoints for testing, trains the classifier
with the rest and reports precision, recall and accuracy for the test
set.
|
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