Overfitting Can Happen Overfitting Can Happen Overfitting Can - PowerPoint PPT Presentation

Nov 25, 2022 •107 likes •138 views

Overfitting Can Happen Overfitting Can Happen Overfitting Can Happen Overfitting Can Happen Overfitting Can Happen 30 25 test 20 error 15 (boosting stumps on heart-disease dataset) train 10 5 0 1 10 100 1000 # rounds

Overfitting Can Happen Overfitting Can Happen Overfitting Can Happen Overfitting Can Happen Overfitting Can Happen 30 25 test 20 error 15 (boosting “stumps” on heart-disease dataset) train 10 5 0 1 10 100 1000 # rounds
Actual Typical Run Actual Typical Run Actual Typical Run Actual Typical Run Actual Typical Run 20 15 error (boosting C4.5 on 10 “letter” dataset) test 5 train 0 10 100 1000 # of rounds ( T ) • test error does not increase, even after 1000 rounds • (total size > 2,000,000 nodes) • test error continues to drop even after training error is zero! # rounds 5 100 1000 train error 0 . 0 0 . 0 0 . 0 test error 8 . 4 3 . 3 3 . 1 • Occam’s razor wrongly predicts “simpler” rule is better
Empirical Evidence: The Margin Distribution Empirical Evidence: The Margin Distribution Empirical Evidence: The Margin Distribution Empirical Evidence: The Margin Distribution Empirical Evidence: The Margin Distribution • margin distribution = cumulative distribution of margins of training examples cumulative distribution 1.0 20 1000 100 15 error 0.5 10 test 5 5 train 0 10 100 1000 -1 -0.5 0.5 1 margin # of rounds ( T ) # rounds 5 100 1000 train error 0 . 0 0 . 0 0 . 0 test error 8 . 4 3 . 3 3 . 1 % margins ≤ 0 . 5 7 . 7 0 . 0 0 . 0 minimum margin 0 . 14 0 . 52 0 . 55

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