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

Technion - Computer Science Department - Ph.D. Thesis PHD-2008-12 - 2008
LSID3-p Tree Size / ID3 Tree Size
LSID3-p Accuracy
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C4.5 Tree Size / ID3 Tree Size
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C4.5 Accuracy
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Figure 3.22: Performance differences for LSID3-p(5) and C4.5. The upper figure
compares the size of trees induced by each algorithm, measured relative to ID3 (in
percents). The lower figure plots the absolute differences in terms of accuracy.
Binary Splits
By default, LSID3 uses multiway splits, i.e., it builds a subtree for each possible
value of a nominal attribute. Following the discussion in Section 3.5.2, we also
tested how LSID3 performs if binary splits are forced. The tests in this case are
found using exhaustive search.
To demonstrate the fragmentation problem, we used two datasets. The first
dataset is Tic-tac-toe. When binary splits were forced, the performance of both
C4.5 and LSID3-p improved from 85.8 and 87.2 to 94.1 and 94.8 respectively. As
in the case of multiway splits, the advantage of LSID3-p over C4.5 is statistically
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