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Table 2 Percentage accuracy of 10-fold cross validation of classification methods for all genes

From: A comparative study of different machine learning methods on microarray gene expression data

Dataset SVM RBF Neural Nets MLP Neural Nets Bayesian J48 Decision Tree Random Forest Id3 Bagging
1. Lymphoma (Devos et.al, 2002) 96.0 84.0 68.0 88.0 64.0 76.0 48.0 52.0
2. Breast Cancer (Perou et. al, 2000) 97.6 97.6 96.4 92.9 92.9 96.4 94.0 96.4
3. Colon Cancer (Alon et. al, 1999) 95.6 91.1 91.1 93.3 91.1 80.0 88.9 93.3
4. Lung Cancer (Garber et. al, 2001) 97.2 97.2 97.2 95.8 94.4 95.8 97.2 97.2
5. Adenocarcinoma (Beer et.al, 2002) 96.5 94.2 75.6 75.6 74.4 79.1 66.3 79.1
6. Lymphoma (Alizadeh et al, 2000) 96.9 88.5 75.0 85.4 75.0 76.0 62.5 84.4
7. Melanoma (Bittner et. al, 2000) 94.7 81.6 84.2 76.3 81.6 81.6 52.6 81.6
8. Ovarian Cancer (Welsh et. al, 2001) 94.9 84.6 89.7 87.2 87.2 89.7 74.4 89.7