anytime algorithms for learning anytime classifiers saher ... - Technion

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Technion - Computer Science Department - Ph.D. Thesis PHD-2008-12 - 2008 Frequency Frequency Frequency 0.25 0.2 0.15 0.1 0.05 0 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 0.3 0.25 0.2 0.15 0.1 0.05 1000 2000 3000 4000 5000 RTG SID3 LSID3 Tree size RTG SID3 LSID3 25 50 75 100 125 150 175 RTG SID3 LSID3 Tree size 0 0 100 200 300 400 500 Tree size Figure B.4: Frequency curves for the Nursery (top), Glass (middle), and Multiplexer- 20 (bottom) datasets 154
Technion - Computer Science Department - Ph.D. Thesis PHD-2008-12 - 2008 Accuracy Accuracy Accuracy 0.95 0.9 0.85 0.8 0.75 0.7 0.65 0.6 0.8 0.75 0.7 0.65 0.6 0.55 0.5 2000 3000 4000 Tree size 0.45 100 110 120 130 140 150 160 0.7 0.65 0.6 0.55 0.5 Tree size 0.45 320 340 360 380 400 420 440 Tree size Accuracy Accuracy Accuracy 0.96 0.94 0.92 0.9 0.88 0.86 0.84 1000 1500 2000 2500 0.95 0.9 0.85 0.8 0.75 0.7 0.65 0.6 0.55 Tree size 0.5 40 45 50 55 60 65 70 75 80 0.85 0.8 0.75 0.7 0.65 0.6 0.55 Tree size 0.5 160 180 200 220 240 260 280 300 Tree size Accuracy Accuracy Accuracy 0.988 0.986 0.984 0.982 0.98 0.978 0.976 0.974 0.972 0.97 550 600 650 700 750 800 0.9 0.85 0.8 0.75 0.7 0.65 Tree size 0.6 34 36 38 40 42 44 46 48 1 0.95 0.9 0.85 0.8 0.75 0.7 0.65 0.6 Tree size 0.55 20 40 60 80 100 120 140 160 Tree size Figure B.5: Correlation between size and accuracy using RTG (left-most), SID3 (middle), and LSID3 (right-most). The upper graphs represent the results for the Nursery dataset, the graphs in the middle row stand for the Glass dataset and the lower graphs stand for the Multiplexer-20 dataset. 155
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anytime algorithms for learning anytime classifiers saher ... - Technion

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