Principal component-based feature selection for tumor classification
Principal component-based feature selection for tumor classification is a scholarly work, published in 2015 in ''Bio-Medical Materials and Engineering''. The main subjects of the publication include independent component analysis, dimensionality reduction, linear discriminant analysis, data mining, artificial intelligence, feature extraction, computer science, curse of dimensionality, facial recognition system, artificial neural network, discriminant, feature, discriminant analysis, principal component analysis, mathematics, pattern recognition, feature selection, and microarray. The paper proposes a new feature selection method for tumor classification using gene expression data.