Description Usage Arguments Value Author(s) References Examples
Generate synthetic positive instances using Safe-level SMOTE algorithm. Using the parameter "Safe-level" to determine the possible location of synthetic instances.
1 |
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 |
C |
The number of nearest neighbors during calculating safe-level process |
dupSize |
The number or vector representing the desired times of synthetic minority instances over the original number of majority instances |
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 |
The value of parameter C for nearest neighbor process used for calculating safe-level |
dup_size |
The maximum times of synthetic minority instances over original majority instances in the oversampling |
outcast |
A set of original minority instances which has safe-level equal to zero and is defined as the minority outcast |
eps |
Unavailable for this method |
method |
The name of oversampling method used for this generated dataset (SLS) |
Wacharasak Siriseriwan <wacharasak.s@gmail.com>
Bunkhumpornpat, C., Sinapiromsaran, K. and Lursinsap, C. 2009. Safe-level-SMOTE: Safe-level-synthetic minority oversampling technique for handling the class imbalanced problem. Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining. 2009, 475-482.
1 2 3 |
[1] "SLS done"
[1] "SLS done"
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