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Table 8 Summary of the performance comparison on applying different classifiers to the colon dataset

From: Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data

Classifier

MR

KIGP(PK)

0.166

KIGP(GK)

0.129

KIGP(LK)

0.198

BagBoost

0.161

Boosting

0.191

RF

0.149

SVM

0.151

PAM

0.119

DLDA

0.129

kNN

0.164

  1. For the KIGP with each of the three different kernel types (PK, GK, LK), we took 5 independent rigorous 3-fold CVs to 62 samples (each CV involves all 3 phases of an KIGP) and reported the average MR. For the 7 referred classifiers, the results and the experimental details were originally reported by[16].
  2. RF: "Random Forests"
  3. PAM: "Nearest shrunken centroids"
  4. DLDA: "diagonal linear discriminant analysis"