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  3. Unsupervised Learning in Python

Exercise

Extracting the cluster labels

In the previous exercise, you saw that the intermediate clustering of the grain samples at height 6 has 3 clusters. Now, use the fcluster() function to extract the cluster labels for this intermediate clustering, and compare the labels with the grain varieties using a cross-tabulation.

The hierarchical clustering has already been performed and mergings is the result of the linkage() function. The list varieties gives the variety of each grain sample.

Instructions

100 XP
  • Import:
    • pandas as pd.
    • fcluster from scipy.cluster.hierarchy.
  • Perform a flat hierarchical clustering by using the fcluster() function on mergings. Specify a maximum height of 6 and the keyword argument criterion='distance'.
  • Create a DataFrame df with two columns named 'labels' and 'varieties', using labels and varieties, respectively, for the column values. This has been done for you.
  • Create a cross-tabulation ct between df['labels'] and df['varieties'] to count the number of times each grain variety coincides with each cluster label.