Machine Learning, Unsupervised Learning, Clustering, K Means.
data df = df.drop(['Region', 'Channel'], axis=1) df.head() from sklearn.cluster import KMeans from sklearn.metrics import silhouette_score # Initialize an empty list to store the silhouette scores scores = [] # Try different numbers of clusters for k in range(2, 11): kmeans = KMeans(n_clusters=k)