Performance Analysis of Feature Selection and Feature Extraction Methods On Biomedical and Healthcare Data
摘要
The work “performance analysis of feature selection and feature extraction methods on Biomedical and Healthcare data on tuberculosis were carried out effectively. The various feature extraction algorithms such as Principal Component Analysis (PCA), Locally Linear Embedding (LLE), Auto Encoder (AE), Independent Component Analysis (ICA) were employed and the performance are analyzed. It is observed that the ICA, i.e. Independent Component Analysis out performs and resulted 95%.