How do I implement SMOTE in Python?

How do I implement SMOTE in Python?

You can implement SMOTE using the imbalanced-learn library. First, install it using pip: pip install imbalanced-learn.

What is the basic code structure for using SMOTE?

Here's a simple example:

from imblearn.over_sampling import SMOTE

# Assuming X_train and y_train are your features and labels
smote = SMOTE()
X_resampled, y_resampled = smote.fit_resample(X_train, y_train)

Are there any parameters I should be aware of?

Yes, you can adjust parameters like sampling_strategy, k_neighbors, and random_state to customize the SMOTE process.

Can I visualize the results after applying SMOTE?

Absolutely! You can use libraries like Matplotlib or Seaborn to visualize the distribution of your resampled data.