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imbalance-handling

Here are 2 public repositories matching this topic...

chipkarsaish / SMOTE-Technique-for-Handling-Imbalance-dataset

SMOTHE is a technique used in machine learning to address imbalance datasets where the minority class has significant fewer instances than the majority class. SMOTHE involves generating Synthetic instances of the minority class by interpolating between existing instances.

pandas dataset numpy-arrays imblearn smote-oversampler oversampling-technique imbalance-handling

Updated Jun 20, 2025
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adityabhardwaj27 / NAFLD_PredictionSystem

Led a project to predict Non-Alcoholic Fatty Liver Disease (NAFLD) using machine learning.

python machine-learning healthcare feature-engineering hyperparameter-tuning enn adasyn imbalance-handling

Updated Dec 28, 2024
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