Spectral Clustering and GMM
How does Spectral Clustering work?
In spectral clustering, the data points are treated as nodes of a graph. Thus, clustering is treated as a graph partitioning problem. The nodes are then mapped to a low-dimensional space that can be easily segregated to form clusters. …
METHODS FOR DETERMINING OPTIMAL NUMBER OF CLUSTERS:
A fundamental step for any unsupervised algorithm is to determine the optimal number of clusters into which the data may be clustered. The Elbow Method is one of the most popular methods to determine this optimal value of k.
HIERARCHICAL AGGLOMERATIVE CLUSTERING:
Implementation code in python:
Also known as bottom-up approach or hierarchical agglomerative clustering (HAC). A structure that is more informative than the unstructured set of clusters returned by flat clustering. This clustering algorithm does not require us to prespecify the number of clusters. …
Word Embeddings are the texts converted into numbers and there may be different numerical representations of the same text.
” Word Embeddings are Word converted into numbers ”
A dictionary may be the list of all unique words in the sentence. …
DBSCAN Clustering Algorithm