Kernel PCA and SVM-RFE based feature selection for classification of dengue microarray dataset

Keyphrases

• Microarray Data 100%
• Feature Selection 100%
• Dengue 100%
• SVM-RFE 100%
• Kernel Principal Component Analysis 100%
• Classification Accuracy 33%
• Suitable Method 16%
• Area under the Curve 16%
• Principal Coordinate Analysis (PCoA) 16%
• Challenging Tasks 16%
• Computation Time 16%
• Classification Performance 16%
• Dengue Fever 16%
• Classification Methods 16%
• Dengue Patients 16%
• Support Vector Machine Classifier 16%
• High-dimensional Data 16%
• Healthy Individuals 16%
• Gene Expression Data 16%
• National Center 16%
• Biotechnology 16%
• Feature Gene 16%
• Time Consumption 16%
• Spatial Structure 16%
• Kernel Methods 16%
• Few Samples 16%
• Binary Class 16%
• High-dimensional Features 16%

Computer Science

• Component Analysis 100%
• Principal Components 100%
• Feature Selection 100%
• Support Vector Machine 100%
• Feature Extraction 100%
• Microarray Data 33%
• Experimental Result 16%
• Classification Accuracy 16%
• Classification Method 16%
• High Dimensional Data 16%
• Classification Performance 16%
• Gene Expression Data 16%
• Computational Time 16%
• Spatial Structure 16%
• Kernel Method 16%
• Time Consumption 16%
• Dimensional Feature 16%