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Table 1 Conservation random forests

From: Conservation machine learning

Feat Info Cl Perf forests Perf jungles Imp
10 3 2 0.85 (0.02) 0.85 (0.02) 0.0%
20 10 3 0.83 (0.02) 0.84 (0.02) 1.2%
50 40 4 0.64 (0.03) 0.69 (0.03) 7.8%
100 90 5 0.49 (0.03) 0.62 (0.03) 26.5%
200 150 6 0.3 (0.03) 0.45 (0.03) 50.0%
300 270 7 0.22 (0.03) 0.35 (0.03) 59.1%
400 350 8 0.18 (0.03) 0.29 (0.03) 61.1%
500 400 9 0.14 (0.02) 0.22 (0.03) 57.1%
1000 500 10 0.11 (0.02) 0.15 (0.03) 36.4%
1000 800 10 0.12 (0.02) 0.17 (0.03) 41.7%
  1. Each line shows the results of 30 replicate experiments, with 5-fold cross validation, 100 independent runs per fold, forests of size 100, and resultant jungles of size 10,000. Feat: number of features in the dataset. Info: number of informative features. Cl: number of target classes. Perf forests: mean performance of forests on test set across all replicates (SD). Perf jungles: mean performance of jungles on test set across all replicates (SD); a jungle’s output was computed through straightforward majority voting. Imp: Percent improvement of Perf jungles vs. Perf forests
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