Fuzzy clustering variation looks for a good subset of attributes in order to improve the classification accuracy of supervised learning techniques in classification problems with a huge number of attributes involved. It first creates a ranking of attributes based on the Variation value, then divide into two groups, last using Verification method to select the best group.Simon Fong, Justin Liang, YanZhuang, "Improving Classification Accuracy Using Fuzzy Clustering Coefficients of Variations (FCCV) Feature Selection Algorithm", 2014 IEEE 15th International Symposium on Computational Intelligence and Informatics (CINTI), pp.147-151

Features

  • fast
  • multiable class
  • All kinds of attribute

Project Samples

Project Activity

See All Activity >

Follow Fuzzy Clustering Coefficient Variation

Fuzzy Clustering Coefficient Variation Web Site

Other Useful Business Software
G-P - Global EOR Solution Icon
G-P - Global EOR Solution

Companies searching for an Employer of Record solution to mitigate risk and manage compliance, taxes, benefits, and payroll anywhere in the world

With G-P's industry-leading Employer of Record (EOR) and Contractor solutions, you can hire, onboard and manage teams in 180+ countries — quickly and compliantly — without setting up entities.
Learn More
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of Fuzzy Clustering Coefficient Variation !

Additional Project Details

Registered

2014-12-20