Chapter 2
Feature Selection for Clustering: A Review
Salem Alelyani
Arizona State UniversityTempe, AZsalelyan@asu.edu
Jiliang Tang
Arizona State UniversityTempe, AZJiliang.Tang@asu.edu
Huan Liu
Arizona State UniversityTempe, AZhuan.liu@asu.edu
2.1 Introduction
The growth of the high-throughput technologies nowadays has led to exponential growth in the harvested data with respect to dimensionality and sample size. As a consequence, storing and processing these data becomes more challenging. Figure (2.1) shows the trend of this growth for UCI Machine Learning Repository. This augmentation made manual processing for these datasets impractical. Therefore, data mining and machine learning tools were proposed to automate pattern recognition and the ...
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