What are imbalanced datasets?
Imbalanced datasets refer to datasets where the distribution of instances across different classes is skewed or uneven. In other words, one class (the majority class) has significantly more examples than one or more other classes (the minority class or classes).
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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