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Chatchai Kasemtaweechok. Improving the performance of k-means clustering to reduce repetitive work by addressing the gap in findings. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2023.
Improving the performance of k-means clustering to reduce repetitive work by addressing the gap in findings
Name: Narongsak Chayangkoon
Organization :
Suratthani Rajabhat University. Faculty of Science and Technology
Email :
narongsak.cha@sru.ac.th
Name: Chatchai Kasemtaweechok
Organization :
Kasetsart University Sriracha Campus. Faculty of Science at Sriracha
Email :
chatchai.ka@ku.th
keyword:
K-means clustering
LCSH:
Cluster analysis
LCSH:
Forest canopy gaps
Abstract:
The k-means clustering algorithm calculates the
distances between data points within each cluster and
determines new centroids for each cluster until the data points
remain unchanged within their respective groups. This process
affects the iteration of the k-means algorithm, leading to an
increase in computation time. Consequently, the overall
execution time of the algorithm is prolonged. This research
presents a process that utilizes the farthest first and canopy
algorithms to reduce the number of iterations in the k-means
clustering. This improvement focuses on enhancing the
centroid initialization method for each cluster. The research
study utilized ten datasets from the UCI machine learning
repository to test the effectiveness of improving the k-means
clustering algorithm. It compares the number of iterations and
the sum of squares error as performance metrics. The results
showed that the farthest first and canopy algorithms
significantly reduce the number of iterations in the k-means
clustering when compared to random centroid initialization.
These research findings confirm the hypothesis that the
method of centroid initialization for each cluster impacts the
iteration process of k-means clustering.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2023
Modified:
2024-04-22
Issued:
2024-04-22
บทความ/Article
application/pdf
BibliograpyCitation :
In Institute of Electrical and Electronics Engineers. The 27th International Computer Science and Engineering Conference 2023 (ICSEC 2023) (pp.148-152). Bangkok : Institute of Electrical and Electronics Engineers
eng
©copyrights King Mongkut's University of Technology North Bangkok
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ใช้เวลา
0.028225 วินาที
Narongsak Chayangkoon
| Title | Contributor | Type |
|---|---|---|
| Improving the performance of k-means clustering to reduce repetitive work by addressing the gap in findings
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Narongsak Chayangkoon;Chatchai Kasemtaweechok | บทความ/Article |
Chatchai Kasemtaweechok
| Title | Contributor | Type |
|---|---|---|
| Improving the performance of k-means clustering to reduce repetitive work by addressing the gap in findings
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Narongsak Chayangkoon;Chatchai Kasemtaweechok | บทความ/Article |