Hybrid optimization for k-means clustering learning enhancement
In recent years, combinational optimization issues are introduced as critical problems in clustering algorithms to partition data in a way that optimizes the performance of clustering. K-means algorithm is one of the famous and more popular clustering algorithms which can be simply implemented and i...
Saved in:
主要作者: | Farhang, Yousef |
---|---|
格式: | Thesis |
語言: | English |
出版: |
2016
|
主題: | |
在線閱讀: | http://eprints.utm.my/id/eprint/78635/1/YousefFarhangPFC2016.pdf |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
相似書籍
-
Privacy preserving data mining using anonymization and K-means clustering on labor dataset
由: Ahmad Zahari, Samahah Solehah
出版: (2019) -
Intrusion detection system using hybrid GSA-k-Means
由: Aslahi, Bibi Masoomeh
出版: (2013) -
Enhancements of kernel learning algorithms for clustering
由: Awan, Abdul Majid
出版: (2007) -
An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
由: Khalaf, Emad Taha
出版: (2019) -
Intrusion detection system using hybird gsa-k-means
由: Aslahi Shahri, Bibi Masoomeh
出版: (2013)