Table 10. Classification performance for hyper-spectral image data set; the numbers between parentheses represent P-values of Welch’s t-test when comparing random forest with the other classifiers.

	Accuracy	Sensitivity	Specificity
Random Forest	95.05% ± 0.34%	94.87% ± 0.35%	95.24% ± 0.54%
Decision Tree	88.59% ± 0.49% (< 2.2e-16)	87.19% ± 0.81% (< 2.2e-16)	89.95% ± 0.73% (< 2.2e-16)
Naïve Bayes	79.69% ± 0.61% (< 2.2e-16)	78.53% ± 0.96% (< 2.2e-16)	80.82% ± 0.95% (< 2.2e-16)
AdaBoost	92.79% ± 0.46% (9.35e-11)	91.31% ± 0.77% (1.173e-10)	94.23% ± 0.58% (0.01189)