A Collection of Oversampling Techniques for Class Imbalance Problem Based on SMOTE

Documentation for package ‘smotefamily’ version 1.3.1

smotefamily-package	A short title line describing what the package does
ADAS	Adaptive Synthetic Sampling Approach for Imbalanced Learning
ANS	Adaptive Neighbor Synthetic Majority Oversampling TEchnique
BLSMOTE	Borderline-SMOTE
DBSMOTE	Density-based SMOTE
gap	The function to provide a random number which is used as a location of synthetic instance
kncount	Counting the number of each class in K nearest neighbor
knearest	The function to find n_clust nearest neighbors of each instance, always removing the index of that instance if it is reported.
n_dup_max	The function to calculate the maximum round each sampling is repeated
RSLS	Relocating Safe-level SMOTE
sample_generator	The function to generate 2-dimensional dataset
SLS	Safe-level SMOTE
SMOTE	Synthetic Minority Oversampling TEchnique
smotefamily	A short title line describing what the package does