TechTowards Data Scienceabout 4 hours ago
Simple Logistic Regression Beats XGBoost on 358 Matches
1 min read
A logistic regression model beat XGBoost, random forest, KNN, and a neural network on a 358-match classification task using 5-fold cross-validation with log-loss as the primary metric. The simplest model won because log-loss penalizes confident mistakes, favoring calibrated probabilities over raw accuracy.
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