What is Weighted Logistic Regression?
- Weighted logistic regression is an extension of standard logistic regression that allows for the incorporation of sample weights into the model.
- In logistic regression, the goal is to model the probability that a binary outcome (e.g., success or failure) occurs as a function of one or more predictor variables. This is typically done using maximum likelihood estimation.
Weighted Logistic Regression for Imbalanced Dataset
In real-world datasets, it’s common to encounter class imbalance, where one class significantly outnumbers the other(s). This class imbalance poses challenges for machine learning models, particularly for classification tasks, as models tend to be biased towards the majority class, leading to suboptimal performance.
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