From: A filter-based feature selection approach for identifying potential biomarkers for lung cancer
 | Classification Algorithms | |||
---|---|---|---|---|
Feature Selection Methods | Support Vector Machine | k-Nearest Neighbor | Naive Bayes | Random Forest |
Information Gain | 0.9031 (6) | 0.9380 (25) | 0.9008 (40) | 0.9206 (50) |
Chi-squared test | 0.8821 (1) | 0.9164 (50) | 0.9151 (4) | 0.9441 (60) |
Relief-F | 0.8821 (1) | 0.9052 (15) | 0.8995 (50) | 0.9306 (60) |
t-test | 0.9067 (15) | 0.9100 (20) | 0.9042 (8) | 0.9304 (40) |
Window t-test | 0.8903 (5) | 0.9216 (5) | 0.9012 (2) | 0.9199 (10) |
Moderated t-test | 0.8903 (6) | 0.9084 (5) | 0.8987 (1) | 0.9309 (50) |
BMI | 0.9077 (4) | 0.9298 (15) | 0.9164 (4) | 0.9250 (9) |