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Table 5 Comparison of performance of similar techniques

From: Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data

Method (Classifier) Number of genes Accuracy
PCA, MLP, Neural Network [1] 96 100%
Nearest Shrunken Centroid [21] 43 100%
Information gain + SVM [26] 150 95%
Towing rule + SVM [26] 150 95%
Sum minority + SVM [26] 150 95%
Max minority + SVM [26] 150 91%
Gini index + SVM [26] 150 95%
Sum of variances + SVM [26] 150 95%
t-statistics + SVM [26] 150 95%
One-dimensional SVM + SVM [26] 150 95%
Information gain + LDA with NCC [20] 4 70%
Chi-squared + NNC [20] 4 70%
Gain Ratio + NNC [20] 4 85%
Gene masking + ANN [22] 13 100%
Gene masking + NCC (this paper) 650 100%
Gene masking + NSCC (this paper) 13 100%