The k-means clustering algorithm is a frequently used algorithm for drawing insights into the formations and separations within data. In marketing, it is often used to build customer segments and understand the behaviors of these different segments. Let's dive into building clustering models in Python.
In order to use the k-means clustering algorithm in the scikit-learn package, we need to import the kmeans module, as shown in the following code:
from sklearn.cluster import KMeans
Then, you can build and fit a k-means clustering model, using the following code:
kmeans = KMeans(n_clusters=4).fit(normalized_df[['TotalSales', 'OrderCount', 'AvgOrderValue']])
As you can see from this code, we are building a clustering model ...
