Build 4-cluster solution
Perfect, you can see the the recommended number of clusters is somewhere between 3 and 4. Now, you will build the latter number of clusters in this exercise.
The normalized RFMT dataset is available as datamart_rfmt_normalized, feel free to use the console to explore it.
Cet exercice fait partie du cours
Customer Segmentation in Python
Instructions
- Import
KMeansfromsklearnlibrary. - Initialize
KMeanswith 4 clusters and random state 1. - Fit k-means clustering on the normalized data set.
- Extract cluster labels and store them as
cluster_labelsobject.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Import KMeans
from ____.____ import ____
# Initialize KMeans
kmeans = ____(____, ____)
# Fit k-means clustering on the normalized data set
____.____(____)
# Extract cluster labels
cluster_labels = ____.____