A Survey on Clustering Based Feature Selection Technique Algorithm for High Dimensional Data
Avinash Godase, Poonam Gupta · 2015
A high dimensional data is enormous issue in data mining and machine learning applications. Feature selection is the mode of recognize the good number of features that produce well-suited outcome as the unique entire set of features. Feature selection process constructs a pathway to reduce the dimensionality and time complexity and also improve the accuracy level of classifier Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of features. In the primary step, features are separated into clusters hence we are study various technique and algorithm such as of graphtheoretic clustering methods a Density-based Clustering Algorithms Distance-based Clustering ,Distributed Clustering Techniques