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Fuzzy Clustering — The soft k-means Which you might not know
Few weeks back I talked about the smarter implementation of k means clustering called K-means ++ clustering. Today, in this story I would be discussing another type of clustering algorithm called Fuzzy Clustering in Machine Learning.
What is a Clustering Algorithm?
Before I jump into the Fuzzy Clustering Algorithm, Let me briefly describe what Clustering Algorithms are …
Clustering is a method of unsupervised learning and is a common technique for statistical data analysis used in many fields. In Data Science, we can use clustering analysis to gain some valuable insights from our data by seeing what groups the data points fall into when we apply a clustering algorithm.
What is Fuzzy Clustering Algorithm?
Fuzzy clustering is a clustering method where data points can belong in more than one group. Computationally, it’s much easier to create fuzzy boundaries than it is to settle on one cluster for one point.
Fuzzy Clustering Algorithm
Fuzzy clustering algorithms are divided into two areas: classical fuzzy clustering and shape-based fuzzy clustering.
