Towards optimal feature and classifier for gene expression classification of cancer

Mathematics

• Back-propagation Neural Network 100%
• Self-organizing Map 84%
• Pearson Correlation 80%
• Feature Selection 76%
• Leukemia 74%
• Gene Expression 72%
• Acute 65%
• Classifier 64%
• Cancer 59%
• DNA Microarray 44%
• Information Gain 43%
• K-nearest Neighbor 38%
• Decision tree 36%
• Signal-to-noise Ratio 36%
• Support Vector Machine 36%
• Mutual Information 34%
• Genomics 33%
• Comparative Study 32%
• Machine Learning 31%
• Correlation coefficient 30%
• Experimental Results 28%
• Demand 28%
• Gene 28%
• Predict 26%
• Coefficient 14%
• Class 8%

Engineering & Materials Science

• Self organizing maps 64%
• Gene expression 62%
• Backpropagation 53%
• Feature extraction 44%
• Classifiers 40%
• Neural networks 34%
• Microarrays 32%
• DNA 29%
• Decision trees 27%
• Genes 27%
• Signal to noise ratio 23%
• Support vector machines 23%
• Machine learning 21%