Eigengap heuristic method to determine the optimal number of clusters
Eigengap heuristic is a technique that can be used to determine the optimal number of clusters. it suggests that the number of clusters is usually given by the value of 'k' that maximizes the eigengap between succeeding eigenvalues. The larger the eigengap is, the closer the eigenvectors of the ideal scenario and, therefore, the better spectral clustering works.
GitHub address: https://github.com/randomaccess2023/M...
Useful resources:
1. Laplacian matrix: https://en.wikipedia.org/wiki/Laplaci...
2. Affinity matrix: https://deepai.org/machine-learning-g...
3. Medium article: / optimal-number-of-clusters-for-spectral-cl...
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