Uses of Interface
adams.core.Randomizable

Packages that use Randomizable

Package	Description
adams.core
adams.data.random
adams.data.splitgenerator
adams.data.splitgenerator.generic.randomization
adams.flow.transformer
adams.flow.transformer.indexedsplitsrunsgenerator
adams.flow.transformer.negativeregions
adams.flow.transformer.preparefilebaseddataset
adams.gui.visualization.image.leftclick
adams.gui.visualization.sequence.pointpreprocessor
adams.ml.evaluation
adams.opt.genetic
adams.opt.optimise
weka.classifiers

Uses of Randomizable in adams.core

Subinterfaces of Randomizable in adams.core

Modifier and Type	Interface	Description
interface	OptionalRandomizable	Interface for classes that have support optional randomization.

Uses of Randomizable in adams.data.random

Subinterfaces of Randomizable in adams.data.random

Modifier and Type	Interface	Description
interface	DistributionBasedRandomNumberGenerator<T extends Number>	Interface for distribution-based random number generators.
interface	SeededRandomNumberGenerator<T extends Number>	Interface for seeded random number generators.

Classes in adams.data.random that implement Randomizable

Modifier and Type	Class	Description
class	AbstractDistributionBasedRandomNumberGenerator<T extends Number>	Ancestor for distribution-based random number generators.
class	AbstractSeededRandomNumberGenerator<T extends Number>	Ancestor for seeded random number generators.
class	JavaRandomByte	Random generator that generates random bytes using Java's java.util.Random class.
class	JavaRandomDouble	Random generator that generates random doubles (0-1) using Java's java.util.Random class.
class	JavaRandomInt	Random generator that generates random integers using Java's java.util.Random class.

Uses of Randomizable in adams.data.splitgenerator

Subinterfaces of Randomizable in adams.data.splitgenerator

Modifier and Type	Interface	Description
interface	CrossValidationFoldGenerator<I,O>	Interface for generating cross-validation folds.
interface	RandomSplitGenerator<I,O>	Interface for generators of random splits of datasets.
interface	SplitGenerator<I,O>	Interface for classes that generate dataset splits.
interface	StratifiableSplitGenerator<I,O>	Interface for split generators that can stratify the randomized data.

Uses of Randomizable in adams.data.splitgenerator.generic.randomization

Classes in adams.data.splitgenerator.generic.randomization that implement Randomizable

Modifier and Type	Class	Description
class	DefaultRandomization	Randomizes the data using a random number generator initialized with the seed value.

Uses of Randomizable in adams.flow.transformer

Classes in adams.flow.transformer that implement Randomizable

Modifier and Type	Class	Description
class	SpreadSheetAnonymize	Anonymizes a range of columns in a spreadsheet.
class	SpreadSheetRandomSystematicSample	Performs random systematic sampling on the rows of the incoming spreadsheet. Divides the rows into N blocks with N being the sample size.
class	WekaAttributeSelection	Performs attribute selection on the incoming data. In case of input in form of a class adams.flow.container.WekaTrainTestSetContainer object, the train and test sets stored in the container are being used. NB: In case of cross-validation no reduced or transformed data can get generated! Input/output: - accepts: weka.core.Instances adams.flow.container.WekaTrainTestSetContainer - generates: adams.flow.container.WekaAttributeSelectionContainer Container information: - adams.flow.container.WekaTrainTestSetContainer: Train, Test, Seed, FoldNumber, FoldCount, Train original indices, Test original indices - adams.flow.container.WekaAttributeSelectionContainer: Train, Reduced, Transformed, Test, Test reduced, Test transformed, Evaluation, Statistics, Selected attributes, Seed, FoldCount
class	WekaBootstrapping	Performs bootstrapping on the incoming evaluation and outputs a spreadsheet where each row represents the results from bootstrapping sub-sample.
class	WekaClassifierRanker	Performs a quick evaluation using cross-validation on a single dataset (or evaluation on a separate test set if the number of folds is less than 2) to rank the classifiers received on the input and forwarding the x best ones.
class	WekaCrossValidationClustererEvaluator	Cross-validates a clusterer on an incoming dataset.
class	WekaCrossValidationEvaluator	Cross-validates a classifier on an incoming dataset.
class	WekaCrossValidationSplit	Generates train/test pairs like during a cross-validation run.
class	WekaRandomSplit	Splits a dataset into a training and test set according to a specified split percentage.

Uses of Randomizable in adams.flow.transformer.indexedsplitsrunsgenerator

Classes in adams.flow.transformer.indexedsplitsrunsgenerator that implement Randomizable

Modifier and Type	Class	Description
class	InstancesCrossValidationFoldGenerator	Split generator that generates folds for cross-validation for Instances objects.
class	InstancesGroupedCrossValidationFoldGenerator	Split generator that generates folds for cross-validation for Instances objects.
class	InstancesGroupedRandomSplitGenerator	Random split generator that works on Instances objects (groups instances).
class	InstancesRandomSplitGenerator	Random split generator that works on Instances objects.
class	ManualSplitGenerator	Uses the manually defined split ranges to generate the splits.
class	SpreadSheetRandomSplitGenerator	Random split generator that works on spreadsheets.

Uses of Randomizable in adams.flow.transformer.negativeregions

Classes in adams.flow.transformer.negativeregions that implement Randomizable

Modifier and Type	Class	Description
class	RandomRegions	Generates specified number of random regions and then prunes ones that overlap with other regions or annotations.

Uses of Randomizable in adams.flow.transformer.preparefilebaseddataset

Classes in adams.flow.transformer.preparefilebaseddataset that implement Randomizable

Modifier and Type	Class	Description
class	AbstractRandomizableFileBasedDatasetPreparation<T>	Ancestor for schemes that randomize the files.
class	CrossValidation	Generates cross-validation folds.
class	GroupedCrossValidation	Generates grouped cross-validation folds.
class	GroupedTrainTestSplit	Generates a train/test split using the specified grouping.
class	GroupedTrainValidateTestSplit	Generates a train/validate/test split using the specified grouping.
class	TrainTestSplit	Generates a train/test split.
class	TrainValidateTestSplit	Generates a train/validate/test split.

Uses of Randomizable in adams.gui.visualization.image.leftclick

Classes in adams.gui.visualization.image.leftclick that implement Randomizable

Modifier and Type	Class	Description
class	RandomBoundingBox	Allows the user to create randomly sized bounding boxes around the left-click position.

Uses of Randomizable in adams.gui.visualization.sequence.pointpreprocessor

Classes in adams.gui.visualization.sequence.pointpreprocessor that implement Randomizable

Modifier and Type	Class	Description
class	Jitter	Adds random jitter to data points, to make it easier to see overlapping ones.

Uses of Randomizable in adams.ml.evaluation

Classes in adams.ml.evaluation that implement Randomizable

Modifier and Type	Class	Description
class	AbstractSplitGenerator	Ancestor for helper classes that generates dataset splits.
class	DefaultCrossValidationFoldGenerator	Helper class for generating cross-validation folds.
class	DefaultRandomSplitGenerator	Generates random splits of datasets.

Uses of Randomizable in adams.opt.genetic

Classes in adams.opt.genetic that implement Randomizable

Modifier and Type	Class	Description
class	AbstractClassifierBasedGeneticAlgorithm	Ancestor for genetic algorithms that evaluate classifiers.
class	AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation	Ancestor for genetic algorithms that offer a second evaluation using a different seed value.
class	AbstractGeneticAlgorithm	Base class for genetic algorithms.
class	DarkLord
class	Hermione	Hermione.
class	PackDataGeneticAlgorithm	???

Uses of Randomizable in adams.opt.optimise

Classes in adams.opt.optimise that implement Randomizable

Modifier and Type	Class	Description
class	RandomOptimiser	Generate random parameter values.

Uses of Randomizable in weka.classifiers

Subinterfaces of Randomizable in weka.classifiers

Modifier and Type	Interface	Description
interface	CrossValidationFoldGenerator	Interface for generating cross-validation folds.
interface	RandomSplitGenerator	Interface for generators of random splits of datasets.
interface	SplitGenerator	Interface for helper classes that generate dataset splits.

Classes in weka.classifiers that implement Randomizable

Modifier and Type	Class	Description
class	AbstractSplitGenerator	Ancestor for helper classes that generates dataset splits.
class	BestBinnedNumericClassRandomSplitGenerator	Picks the best binning algorithm from the provided ones.
class	BinnedNumericClassCrossValidationFoldGenerator	Helper class for generating cross-validation folds.
class	BinnedNumericClassRandomSplitGenerator	Generates random splits of datasets with numeric classes using a binning algorithm.
class	DefaultCrossValidationFoldGenerator	Helper class for generating cross-validation folds.
class	DefaultRandomSplitGenerator	Generates random splits of datasets.
class	GroupedBinnedNumericClassCrossValidationFoldGenerator	Helper class for generating cross-validation folds.
class	GroupedBinnedNumericClassRandomSplitGenerator	Generates random splits of datasets with numeric classes using a binning algorithm.
class	GroupedCrossValidationFoldGenerator	Helper class for generating cross-validation folds.
class	GroupedCrossValidationFoldGeneratorUsingNumericClassValues	Helper class for generating cross-validation folds. Uses the string representation of the numeric class values as grouping.
class	GroupedRandomSplitGenerator	Generates random splits of datasets, making sure that groups of instances stay together (identified via a regexp).
class	LeaveOneOutByValueGenerator	Generates train/test split pairs using the unique values from the specified attribute.
class	MultiLevelSplitGenerator	Generates splits based on groups extracted via regular expressions.