Review of Feature Selection Techniques for Predicting Diseases

Abstract

Machine learning has a significant impact on healthcare organization to predict the disease as early as possible, but the dataset received will have noisy data like duplicate and not relevant features which impact the validation and accuracy level. Feature selection can be used to reduce these noisy data and can be used for both the Regression and Classification problems. This paper is to analyze different feature selection methods that can be applied in machine learning techniques, which can be used in the healthcare industry for effectively predicting several diseases.