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Table 4 Experiment 1: Classification Accuracy with Random Forest

From: Supervised Regularized Canonical Correlation Analysis: integrating histologic and proteomic measurements for predicting biochemical recurrence following prostate surgery

Dataset (ϕP, ϕJ) CCA RCCA SRCCA TT SRCCA WRST SRCCA WLT
(ϕP, ϕM) 37% 42% 83% 81% 84%
(ϕP, ϕA) 74% 30% 81% 77% 83%
(ϕP, ϕH) 62% 42% 91% 89% 93%
  1. Classification accuracies obtained for fusing (ϕP, ϕM), (ϕP, ϕA), and (ϕP, ϕH), with CCA, RCCA, SRCCA TT , SRCCA WRST , and SRCCA WLT using the top d = 3 components, using ϕRFwith 50 trees and leave-one-out validation to identify patients at the risk of biochemical recurrence from those who are not.