Hands-On Machine Learning with C++

Summary

In this chapter, we considered what clustering is and how it differs from classification. We saw different types of clustering methods, such as the partition-based, the spectral, the hierarchical, the density-based, and the model-based methods. Also, we observed that partition-based methods could be divided into more categories, such as the distance-based methods and the ones based on graph theory. We used implementations of these algorithms, including the k-means algorithm (the distance-based method), the GMM algorithm (the model-based method), the Newman modularity-based algorithm, and the Chinese Whispers algorithm for graph clustering. We also saw how to use the hierarchical and spectral clustering algorithm implementations in ...