clustering models

Today, I built three clustering models for sonic log.

Summary:

Three models are:
1. k-means clustering
2. density-based spatial clustering of applications with noise (DBSCAN)
3. expectation maximization algorithm for gaussian mixture model (EM GMM)
The following are results of two clusters and three clusters.

Two clusters

Three clusters

From two figures, I think that two clusters performs better than three clusters. For k-means, it includes medium and poor clusters together and for DBSCAN and EM GMM, they include good and medium clusters together.

Tomorrow, I will try to improve the results.