Example usage for weka.filters SupervisedFilter interface-usage

Introduction

In this page you can find the example usage for weka.filters SupervisedFilter interface-usage.

Usage

From source file org.packDataMining.SMOTE.java

/**
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 * Resamples a dataset by applying the Synthetic Minority Oversampling TEchnique (SMOTE). The original dataset must fit entirely in memory. The amount of SMOTE and number of nearest neighbors may be specified. For more information, see <br/>
 * <br/>
 * Nitesh V. Chawla et. al. (2002). Synthetic Minority Over-sampling Technique. Journal of Artificial Intelligence Research. 16:321-357.
 * <p/>

From source file resample.OverSubsample.java

/** 
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 * Produces a random subsample of a dataset. The original dataset must fit entirely in memory. This filter allows you to specify the maximum "spread" between the rarest and most common class. For example, you may specify that there be at most a 2:1 difference in class frequencies. When used in batch mode, subsequent batches are NOT resampled.
 * <p/>
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 *