org.openimaj.experiment.dataset.sampling

Class StratifiedGroupedUniformRandomisedSampler<KEY,INSTANCE>

java.lang.Object

org.openimaj.experiment.dataset.sampling.StratifiedGroupedUniformRandomisedSampler<KEY,INSTANCE>

Type Parameters:

KEY - Type of groups

INSTANCE - Type of instances

All Implemented Interfaces:

Sampler<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>

public class StratifiedGroupedUniformRandomisedSampler<KEY,INSTANCE>
extends Object
implements Sampler<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>

A stratified uniformly random sampling scheme for grouped datasets. Both sampling with and without replacement are supported. The sampler returns a dataset that selects a predefined fraction of the input data. Specifically, the given percentage of data is selected from each group independently, thus ensuring that the distribution of relative group sizes before and after sampling remains (approximately) constant.

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk)

Constructor Summary

Constructors

Constructor and Description
StratifiedGroupedUniformRandomisedSampler(double percentage) Construct a StratifiedGroupedUniformRandomisedSampler with the given percentage of instances to select.
StratifiedGroupedUniformRandomisedSampler(double percentage, boolean withReplacement) Construct a StratifiedGroupedUniformRandomisedSampler with the given percentage of instances to select, using with with-replacement or without-replacement sampling.
StratifiedGroupedUniformRandomisedSampler(int number) Construct a StratifiedGroupedUniformRandomisedSampler with the given number of instances to select.
StratifiedGroupedUniformRandomisedSampler(int number, boolean withReplacement) Construct a StratifiedGroupedUniformRandomisedSampler with the given number of instances to select, using with with-replacement or without-replacement sampling.

Method Summary

Methods

Modifier and Type	Method and Description
GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>	sample(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> dataset) Perform the sampling operation on the given data and return the sampled dataset.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

StratifiedGroupedUniformRandomisedSampler

public StratifiedGroupedUniformRandomisedSampler(double percentage)

Construct a StratifiedGroupedUniformRandomisedSampler with the given percentage of instances to select. By default, the sampling is without replacement (i.e. an instance can only be selected once).

Parameters:

percentage - percentage of instances to select

StratifiedGroupedUniformRandomisedSampler

public StratifiedGroupedUniformRandomisedSampler(double percentage,
                                         boolean withReplacement)

Construct a StratifiedGroupedUniformRandomisedSampler with the given percentage of instances to select, using with with-replacement or without-replacement sampling.

Parameters:

percentage - percentage of instances to select

withReplacement - should the sampling be performed with replacement (true); or without replacement (false).

StratifiedGroupedUniformRandomisedSampler

public StratifiedGroupedUniformRandomisedSampler(int number)

Construct a StratifiedGroupedUniformRandomisedSampler with the given number of instances to select. By default, the sampling is without replacement (i.e. an instance can only be selected once).

Parameters:

number - number of instances to select

StratifiedGroupedUniformRandomisedSampler

public StratifiedGroupedUniformRandomisedSampler(int number,
                                         boolean withReplacement)

Construct a StratifiedGroupedUniformRandomisedSampler with the given number of instances to select, using with with-replacement or without-replacement sampling.

Parameters:

number - number of instances to select

withReplacement - should the sampling be performed with replacement (true); or without replacement (false).

Method Detail

sample

public GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> sample(GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE> dataset)

Description copied from interface: Sampler

Perform the sampling operation on the given data and return the sampled dataset.

Specified by:

sample in interface Sampler<GroupedDataset<KEY,ListDataset<INSTANCE>,INSTANCE>>

Parameters:

dataset - the dataset to sample

Returns:

the sampled dataset