paveethrans / customer-spendingscore-segmentation

In this project, I apply an unsupervised - clustering algorithm to segregate(cluster) customers based on factors such as his/her Spending score in a mall, Frequency of visiting the mall etc.

Customer-SpendingScore-Segmentation

In this project, I apply an unsupervised - clustering algorithm to segregate(cluster) customers based on factors such as his/her Spending score in a mall, Frequency of visiting the mall etc. After a through data preprocesing and dimensionality reduction methods, P.S. THE GIVEN DATASET (MALL_CUSTOMERS.CSV) IS ALREADY PREPROCESSED AND IS READY FOR TRAIN AND TEST. I train the data on K-Means Clustering model as well as Heirarchical clustering model, to form K (here 4) clusters, and the optimal number of clusters were found out from the Elbow method using WCSS. WCSS- Within cluster sum of squares.

You can find my code and corresponding output of test data clustered graph in the folder above.

customer-spendingscore-segmentation's Issues

Text Formatting Error!

In your kmeansclust.py file on line 32 you've spaced wrongly in the middle.
It should be "IS OPTIMUM" but you've spelled "I SOPTIMUM"!
I think so!
My First Issue😍