adas: Adaptive Synthetic Sampling Approach for Imbalanced Learning

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

Description

Generate synthetic positive instances using ADASYN algorithm. The number of majority neighbors of each minority instance determines the number of synthetic instances generated from the minority instance.

Usage

ADAS(X,target,K=5)

Arguments

X	A data frame or matrix of numeric-attributed dataset
target	A vector of a target class attribute corresponding to a dataset X.
K	The number of nearest neighbors during sampling process

Value

data	A resulting dataset consists of original minority instances, synthetic minority instances and original majority instances with a vector of their respective target class appended at the last column
syn_data	A set of synthetic minority instances with a vector of minority target class appended at the last column
orig_N	A set of original instances whose class is not oversampled with a vector of their target class appended at the last column
orig_P	A set of original instances whose class is oversampled with a vector of their target class appended at the last column
K	The value of parameter K for nearest neighbor process used for generating data
K_all	Unavailable for this method
dup_size	A vector of times of synthetic minority instances over original majority instances in the oversampling in each instances
outcast	Unavailable for this method
eps	Unavailable for this method
method	The name of oversampling method used for this generated dataset (ADASYN)

Author(s)

Wacharasak Siriseriwan <[e-mail]>

References

He, H., Bai, Y., Garcia, E. and Li, S. 2008. ADASYN: Adaptive synthetic sampling approach for imbalanced learning. Proceedings of IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference. pp.1322-1328.

Examples

data_example = sample_generator(10000,ratio = 0.80)
genData = ADAS(data_example[,-3],data_example[,3])
genData_2 = ADAS(data_example[,-3],data_example[,3],K=7)

smotefamily documentation built on May 30, 2019, 9:01 a.m.