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  • SMOTE for Imbalanced Classification with Python
    SMOTE-NC is a variant of SMOTE that is suitable for datasets containing a mix of nominal (categorical) and continuous features It modifies the SMOTE algorithm to correctly handle categorical data The traditional SMOTE algorithm excels in generating synthetic samples to address class imbalance in datasets with only numerical features
  • SMOTE — Version 0. 14. dev0 - imbalanced-learn
    SMOTE (*, sampling_strategy = 'auto', random_state = None, k_neighbors = 5) [source] # Class to perform over-sampling using SMOTE This object is an implementation of SMOTE - Synthetic Minority Over-sampling Technique as presented in Read more in the User Guide Parameters:


















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