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.
Este exercício faz parte do curso
Customer Segmentation in Python
Instruções do exercício
- Import
KMeansfrom thescikit-learnlibrary. - Initialize
KMeanswith 3 clusters and random state 1. - Fit k-means clustering on the normalized data set.
- Extract cluster labels and store them as
cluster_labels.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# 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 = ____.____