Run k-means
You will now build a 3 clusters with k-means clustering. We have loaded the pre-processed RFM dataset as datamart_normalized
. We have also loaded the pandas
library as pd
.
You can explore the dataset in the console to get familiar with it.
This exercise is part of the course
Customer Segmentation in Python
Exercise instructions
- Import
KMeans
from thescikit-learn
library. - Initialize
KMeans
with 3 clusters and random state 1. - Fit k-means clustering on the normalized data set.
- Extract cluster labels and store them as
cluster_labels
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Import KMeans
from ____.____ import ____
# Initialize KMeans
kmeans = ____(____=3, ____=1)
# Fit k-means clustering on the normalized data set
____.____(datamart_normalized)
# Extract cluster labels
cluster_labels = ____.____