Plot Silhouette scores for GMM models

Art027_Python_005.py

# Create empty list
S=[]

# Range of clusters to try (2 to 10)
K=range(2,11)

# Select data for clustering model
X = df_loc[['Latitude', 'Longitude']]

for k in K:
    # Set the model and its parameters
    model = GaussianMixture(n_components=k, n_init=20, init_params='kmeans')
    # Fit the model 
    labels = model.fit_predict(X)
    # Calculate Silhoutte Score and append to a list
    S.append(metrics.silhouette_score(X, labels, metric='euclidean'))

# Plot the resulting Silhouette scores on a graph
plt.figure(figsize=(16,8), dpi=300)
plt.plot(K, S, 'bo-', color='black')
plt.xlabel('k')
plt.ylabel('Silhouette Score')
plt.title('Identify the number of clusters using Silhouette Score')
plt.show()