Figure 1.

Performance of CP-RF on pima. We perform CP-RF by applying a ten-fold cross validation in online learning setting and report the average performance. To apperceive how accurate and effective the prediction region is, we use 4 evaluation indices at each predefined significance level: (1) Percentage of certain predictions. (2) Percentage of uncertain predictions with two or more labels which indicates that all these labels are likely to be correct. (3) Percentage of empty predictions. (4) Percentage of corrective predictions which give the proportion of test examples classified correctly. These terms are extended by conformal predictor and distinguish with traditional accuracy rate given by RF, SVM and other traditional classifiers.