Pragmatic Machine Learning with Python by Avishek Nag

Author:Avishek Nag [Nag, Avishek]
Language: eng
Format: epub
ISBN: 9789389845365
Publisher: BPB Publications
Published: 2020-07-15T00:00:00+00:00

Where N = the size of the total data set.

Value for any Silhouette Coefficient ranges between – 1 to +1. A bigger value indicates bigger inter-cluster distance and lesser inner-cluster error and thus a better overall cluster setup. A negative Silhouette Coefficient for a data point indicates that it has been assigned to a wrong cluster, and overall negative measure says most of the data points are wrongly assigned.

Python implementation of cluster metric

The scikit-learn provides two functions for computing the overall Silhouette Coefficient of the complete cluster setup as well as individual Silhouette Coefficient for each data point. It takes features and predicted cluster labels as input. We will use computed pca_vectors in the previous section as features:

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