SPECTRAL CLUSTERING USING SPIRAL DYNAMICS OPTIMIZATION AND ITS APPLICATION TO DNA MICROARRAY DATA
There are many methods that can be used for clustering. K-means is one of the most commonly used method. Using K-means in clustering depends on the selection of the initial cluster centers that could be stuck on a non optimal solution. Spiral dynamics optimization is metaheuristics methods used to f...
Saved in:
| Main Author: | |
|---|---|
| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/23007 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | There are many methods that can be used for clustering. K-means is one of the most commonly used method. Using K-means in clustering depends on the selection of the initial cluster centers that could be stuck on a non optimal solution. Spiral dynamics optimization is metaheuristics methods used to find a solution that near <br />
<br />
optimum. Spiral clustering is constructed using this methods. Spectral clustering closely related to eigenvectors also discussed for data clustering. This method is derived based on Ncut and more powerful than 2 methods before. Besides that, the meaning of the second and third eigenvector related to clustering is also discussed. In the end, these methods are applied to the DNA microarray data. |
|---|