| SMOTE {smotefamily} | R Documentation |
Synthetic Minority Oversampling TEchnique
Description
Generate synthetic positive instances using SMOTE algorithm
Usage
SMOTE(X, target, K = 5, dup_size = 0)
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 |
dup_size |
The number or vector representing the desired times of synthetic minority instances over the original number of majority instances |
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 |
The maximum times of synthetic minority instances over original majority instances in the oversampling |
outcast |
Unavailable for this method |
eps |
Unavailable for this method |
method |
The name of oversampling method used for this generated dataset (SMOTE) |
Author(s)
Wacharasak Siriseriwan <wacharasak.s@gmail.com>
References
Chawla, N., Bowyer, K., Hall, L. and Kegelmeyer, W. 2002. SMOTE: Synthetic minority oversampling technique. Journal of Artificial Intelligence Research. 16, 321-357.
Examples
data_example = sample_generator(10000,ratio = 0.80)
genData = SMOTE(data_example[,-3],data_example[,3])
genData_2 = SMOTE(data_example[,-3],data_example[,3],K=7)