logistic regression

balanced weight for imbalanced classification model

Balanced Weights For Imbalanced Classification

The balanced weight is one of the widely used methods for imbalanced classification models. It modifies the class weights of the majority and minority classes during the model training process to achieve better model results. Unlike the oversampling and under-sampling methods, the balanced weights methods do not modify the minority and majority class ratio. Instead, …

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LASSO (L1) vs Ridge (L2) vs Elastic Net Regularization for Classification Model

LASSO (L1) vs Ridge (L2) vs Elastic Net Regularization for Classification Model

LASSO (Least Absolute Shrinkage and Selection Operator) is also called L1 regularization, and Ridge is also called L2 regularization. Elastic Net is the combination of LASSO and Ridge. All three are techniques commonly used in machine learning to correct overfitting. In this tutorial, we will cover Resources for this post: Step 0: LASSO (L1) vs …

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