ubSmoteExs

data

the index of the target/response variables

N/100 is the number of new instances generated for each rare instance. 
      If N < 100 a single instance is generated

the number of neighbours to consider as the pool from where the new examples are generated

Function used in SMOTE to generate new minority examples.

A dataset is said to be unbalanced when the class of interest (minority class) is much rarer than normal behaviour (majority class). The cost of missing a minority class is typically much higher that missing a majority class. Most learning systems are not prepared to cope with unbalanced data and several techniques have been proposed. This package implements some of most well-known techniques and propose a racing algorithm to select adaptively the most appropriate strategy for a given unbalanced task.

ubSmoteExs: ubSmoteExs

Description

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See Also