Exploring Different Feature Selection Techniques for High Risk Disease prediction using Machine Learning

Feature selection is one of the important step in feature reduction in data science. High dimensional data generally have extra or redundant features because of which overfitting problem may occur and performance may get degraded. There are number of different feature selection techniques are present. The application of feature selection is in different task of data science like classification, clustering, regression etc. The objective of the research is to study all different types of feature selection methods in detail. This review gives detailed information about all these methods which are applied in different application area to select the most important features and removes redundant or irrelevant features.