Improving K-means through better initialization and normalization
- Resource Type
- Authors
- Manoj K. Singh; Prashant K. Sharma; Akanksha Choudhary
- Source
- ICACCI
- Subject
- Normalization (statistics)
business.industry
Computer science
k-means clustering
Initialization
Pattern recognition
02 engineering and technology
computer.software_genre
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Artificial intelligence
Data mining
business
Cluster analysis
computer
- Language
K-means is still a popular clustering algorithm and active research area. The research is majorly focused at improving efficiency and effectiveness of the method. This paper proposes combined approach of a ranked initialization and normalization of data values with k-means. Three variations of a score based initialization approach is proposed. Experiments are performed on normalized data to prove the superiority of the proposed algorithm.