Get the Optimal K in K-Means Clustering

Author(s): Satsawat Natakarnkitkul

Originally published on Towards AI.

Provide the quick starting guide to find the optimal number of clusters in K-means clustering

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Photo by Fotis Fotopoulos on Unsplash

Clustering (or Cluster Analysis) helps to identify and group the data points, which is closely related using some measure of distance, to a blob of data or segment. Clustering is classified as unsupervised learning within machine learning space, this means there is no labeled.

It is one of the important techniques in machine learning for business or corporate utilizing data science. Several use cases are:

In the financial industry, suspicious activities and individuals can be identified using anomaly detectionIn biology, clustering is used to find groups of genes with similar property or expression patternsIn marketing science,… Read the full blog for free on Medium.

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Published via Towards AI