New Book 'Imbalanced Data' Debunks Common Myths in Classification Models
Al_Grigor · x · 2026-08-15
Recommends the new book 'Imbalanced Data: Myths, Mistakes and Modern Solutions' by Soledad Galli. Based on experiments across 37 datasets, it tests widely accepted approaches like model choice, probability calibration, and decision thresholds to correct common mistakes in handling imbalanced classification data.
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