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

Documentation for package ‘smotefamily’ version 1.4.0

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	SMOTE family package for Data Generation