CTGAN-ENN

CTGAN-ENN : Tabular GAN-based Hybrid sampling method.

• A sampling method that combine CTGAN (Conditional Tabular GAN) and ENN(Edited Nearest Neighboor)
• CTGAN is a powerfull oversampling method based on GAN for tabular data
• ENN is an efficient undersampling method to remove overlapped data

Installation

Install CTGAN-ENN using pip:

pip install ctganenn

Usage

Variables

• minClass: the minority class in the dataset (dataframe).
• majClass: the majority class in the dataset (dataframe).
• genData: how much data that you want generate from minorty class.
• targetLabel: what is your target label name in dataset.

Example Usage

from ctganenn import CTGANENN

use the CTGANENN function with 4 variables

CTGANENN(minClass,majClass,genData,targetLabel)

Output

the output of method are X and y :

• X : all features of your dataset
• y : target label of your dataset

Classification process

you can process the X and y variable to the next step for classification stage. For example using Decision Tree Classifier:

model = tree.DecisionTreeClassifier()
classification = model.fit(X, y)

Limitation

CTGAN-ENN on this version only works for binary classification