Table 1.
Description of datasets used for evaluation and comparison.
Table 2.
The resultant BSTs after applying EPBST and RPBST in the training phase on 80% of data, time in (ms).
Table 3.
Accuracy results of MR-KNN and KNN-IS compared to the proposed methods in the test stage with 5-fold-CV.
Table 4.
Speed-up comparison of MR-KNN and KNN-IS, with 5-fold-CV.
Table 5.
Accuracy results of RC-KNN and LC-KNN compared to the proposed methods in the test stage, with 10-fold-CV.
Table 6.
Speed-up comparison of RC-KNN and LC-KNN, with 10-fold-CV.
Table 7.
Classification accuracy comparison of RPBST, EPBST and KNN, with 5-fold-CV.
Table 8.
Accuracy results of MDT1and MDT2 compared to the proposed methods in the test stage, with different test ratios.
Table 9.
Speed-up comparison of MDT1, and MDT2, with different test ratios.