[Skip to Content]
 
 
  • Departments
  • Quick Links
  • A-Z
 
  •  
  • My Account
  • Profiles
  • Webmail
  • About Us

    About Us

      1. About CU
      2. Mission
      3. Our Core Values
      4. Our History
      5. Inside Covenant
      6. Focus
      7. The Chancellor
      8. The Vice Chancellor
      9. The Deputy Vice Chancellor
      10. The Registrar
      1. Chaplaincy
      2. Academic Affairs Office
      3. Centre for Systems and Information Services (CSIS)
      4. Media and Corporate Affairs Directorate
      5. Unique Programmes
      6. Student Affairs
      7. Campus Security
      8. Financial Services
      9. Community Impact
      10. Academic Planning
      1. Counselling Centre
      2. Covenant University Medical Centre
      3. Centre for Entrepreneurial Development Studies
      4. International Office and Linkages
  • Admissions

    Admissions

      1. Undergraduate Admission
      2. Postgraduate Admission
      3. Foreign Students Admission
  • Colleges

    Colleges

      1. College of Business and Social Sciences
      2. College of Engineering
      3. College of Leadership Development Studies
      4. College of Science and Technology
      5. School of Postgraduate Studies
  • Library
  • News
  • Research
  • Covenant Journals
  • Academic Calendar
  • Covenant OER
  • Payment
  • Give

    Give to Covenant

      1. Research
      2. Community Development
Reducing the time requirement of k-means Algorithm.
  • Home
  • »
  • Profiles
  • »
  • Oyelade Olanrewaju Jelili
  • »
  • Reducing the time requirement of k-means Algorithm.

Reducing the time requirement of k-means Algorithm.

~ Bddf58dbb411cefd645e70c20debcc32.200x200
Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in ddimensional space Rd and an integer k. The problem is to determine a set of k points in Rd, called centers, so as to minimizethe mean squared distance...
 
Published at PloS One Journal Vol. 7(12) (IF: 4.25).
Published in 2014
 
Download 177.73 kB
 
visit (http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0049946, http://www.ncbi.nlm.nih.gov/pubmed?term=oyelade)
 
 
Oyelade, O.J.
Oyelade Olanrewaju Jelili » Dr. Oyelade, Olanrewaju Jelili Received his Bachelor Degree in Computer Science with Mathematics (Combined Honour) and M.Sc. in Computer Science from Obafemi Awolowo University, Ile-Ife, Nigeria and Ph.D in Covenant University, Ota, Nigeria. He is a Faculty member in the Department of Computer and Information Sciences, Covenant University, Nigeria. His current research interests include... view full profile
Oyelade Olanrewaju Jelili
 
Other publications by this author (view profile)
 
 
Application of Fizzy Logic in Decision Making on Student’s academic performance.
 
Effect of Update Anomalies on Herbarium Database Disk Assess
 
Normalization of plant database of a Herbarium
 
A comparison of Fuzzy and Deterministic Models for assessing Students’ Performance.
 
The Design and Implementation of Online Medical Record System (OMRS)
 
Design and Implementation of a Mobile Airline Reservation System
 
Application of Fuzzy Association Rule Mining for Analysing Students Academic Performance
 
Designed and Implementation of Meeting Document Management and Retrieval System
 
Comparative Analyses between Split and HierarchyMap Treemap Algorithms for Visualizing Hierarchical Data.
 
Implementing A Decision-Making Model for a Small Scale Production Company
 
A Two-Phase Dynamic Programming Algorithm Tool for DNA Sequences
 
Design and Implementation of Text To Speech Conversion for Visually Impaired People
 
Computational Identification of Signalling Pathways in Plasmodium falciparum”
  • ©2019 Covenant University | Sitemap | Contact Us
    •  
    •  
    •  
    •  
    •  
    •  
    •