ICP_6 - acvc279/Python_Deeplearning GitHub Wiki

Video Link: https://drive.google.com/file/d/1etuJhvAercYCeFTgqKo9dJhXqKKUlCi_/view?usp=drivesdk

1. Apply K means clustering in thedata set provided below:

  • Remove any null values by the mean.

  • Use the elbow method to find a good number of clusters with the KMeans algorithm

  • Calculate the silhouette score for the above clustering

Removed all the null values of two colomns which are CREDIT_LIMIT and MINIMUM_PAYMENTS We used the Elbow model to find the kmeans value then we find the silhouette score which about 0.46.

Try feature scalingand then apply KMeans on the scaled features. Did that improve the Silhouette score? If Yes, can you justify why

First we removed null values found scalinging by using we applied k means again we found silhouette value and got 0.19 when k=4 Here we found that there is no increse the score of silhouette.

Apply PCA on the same dataset.Apply kMeans algorithm on the PCA result and report your observation if the silhouette score improved or not?

First we clear the the null values of data set. We perform PCM WE found kmeans then we got the silhouette score of about 0.40

Learned from this icp Kmeans, PCM,Scaling