find optimal number of clusters sklearn
# Import library
from clusteval import clusteval
# Set parameters, as an example dbscan
ce = clusteval(method='dbscan')
# Fit to find optimal number of clusters using dbscan
results= ce.fit(X)
# Make plot of the cluster evaluation
ce.plot()
# Make scatter plot. Note that the first two coordinates are used for plotting.
ce.scatter(X)
# results is a dict with various output statistics. One of them are the labels.
cluster_labels = results['labx']