geometric-smote python

Geometric-SMOTE is an oversampling technique for imbalanced data sets that generates synthetic minority class samples based on the k-nearest neighbors algorithm. Here is an example of how to use Geometric-SMOTE in Python:

from imblearn.over_sampling import GeometricSMOTE

# X_train is your input features and y_train is your target variable
smote = GeometricSMOTE()
X_train_resampled, y_train_resampled = smote.fit_resample(X_train, y_train)

In this example, `X_train` and `y_train` are your original input features and target variable, respectively. The `fit_resample` method of the `GeometricSMOTE` class generates synthetic samples for the minority class and returns the resampled input features and target variable.

Note that you need to install the `imblearn` package to use Geometric-SMOTE. You can install it using pip:

pip install -U imbalanced-learn