Tutorial
Jun 26, 202612 min read
0
Bagging and Boosting: Ensemble Intuition
You're building a loan approval system. A single decision stump catches 7 of 8 borderline cases, but the one it misses — a borrower whose income sits just above…
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Ensemble
Tutorial
Jun 26, 202611 min read
0
Random Forest: Algorithm and Regression
You've trained a bagged ensemble on your house price data — bootstrap three samples, grow three trees, average the predictions. The variance dropped, but not as…
Tutorial
Jun 26, 202610 min read
0
Random Forest: Feature Importance and Feature Engineering
Your Random Forest model reports 79% accuracy on the diabetes test set. The stakeholder asks: "Which factors drive the prediction?" You know it's Glucose, BMI,…
Tutorial
Jun 26, 202613 min read
0
Random Forest: Forest Cover Type Project
You've deployed a Random Forest to classify forest cover types from cartographic data. The model handles 54 features, predicts 7 tree species, runs in productio…
Tutorial
Jun 26, 202611 min read
0
AdaBoost: Algorithm Intuition
Your loan default model uses a single decision stump — one rule like "income ≤ 55k → default." Accuracy: 88%, barely better than guessing. The boss asks for 95%…