Improving Clustering Method Performance Using K-Means, Mini Batch K-Means, BIRCH and Spectral
Author:
Affiliation:
1. Institut Teknologi Telkom Purwokerto,Department of Informatics,Banyumas,Indonesia
2. Institut Teknologi Telkom Purwokerto,Department of Data Science,Banyumas,Indonesia
3. School of Computing, Telkom University,Bandung,Indonesia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9702758/9702759/09702823.pdf?arnumber=9702823
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1. Analysis of K-means, DBSCAN and OPTICS Cluster Algorithms on Al-Quran Verses
2. Complex Data Imputation by Auto-Encoders and Convolutional Neural Networks—A Case Study on Genome Gap-Filling
3. New Routes from Minimal Approximation Error to Principal Components
4. Comparative study of k-means and mini batch k-means clustering algorithms in android malware detection using network traffic analysis
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