Package com.rapidminer.operator.preprocessing.sampling

Preprocessing operators used for sampling.

See:
Description

Class Summary

AbsoluteSampling	Absolute sampling operator.
AbsoluteStratifiedSampling	Stratified sampling operator.
AbstractBootstrapping	This operator constructs a bootstrapped sample from the given example set.
AbstractSamplingOperator	Abstract superclass of operators leaving the attribute set and data unchanged but reducing the number of examples.
AbstractStratifiedSampling	Abstract superclass of stratified sampling operators.
Bootstrapping	This operator constructs a bootstrapped sample from the given example set.
KennardStoneSampling	This operator performs a Kennard-Stone Sampling.
ModelBasedSampling	Sampling based on a learned model.
PartitionOperator	Divides a data set into the defined partitions and deliver the subsets.
RatioStratifiedSampling	Stratified sampling operator.
SimpleSampling	Simple sampling operator.
WeightedBootstrapping	This operator constructs a bootstrapped sample from the given example set which must provide a weight attribute.

Package com.rapidminer.operator.preprocessing.sampling Description

Preprocessing operators used for sampling.