X_train, y_train = smote.fit_resample(X_train, y_train)

This code snippet is using the SMOTE (Synthetic Minority Over-sampling Technique) algorithm to oversample the training data.

The "fit_resample" method of the SMOTE object is called with the training data X_train and y_train as inputs. This method fits the SMOTE model on the training data and generates new synthetic samples for the minority class to balance the class distribution.

The new oversampled X_train and y_train are returned and can be used to train a machine learning model with a balanced class distribution.