Unsupervised machine learning (e.g. k-means, GMM) can be used to segment data into various clusters. But how do you know the optimal number of clusters to divide your data? This video explains the use of AIC / BIC to identify the optimal number of parameters for unsupervised models.
The code from this video is available at: github.com/bnsreenu/python_fo...
Негізгі бет Ғылым және технология 53 - How to pick optimal number of parameters for your unsupervised machine learning model?
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