Perform Principal component analysis and perform clustering using first 3 principal component scores (both heirarchial and k mean clustering(scree plot or elbow curve) and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data (class column we have ignored at the begining who shows it has 3 clusters)
PCA Implementation
Checking with other Clustering Algorithms
1.Hierarchical Clustering
2.K-Means Clustering
Build Cluster algorithm using K=3
-
Notifications
You must be signed in to change notification settings - Fork 0
Perform Principal component analysis and perform clustering using first 3 principal component scores (both heirarchial and k mean clustering(scree plot or elbow curve) and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data (class column we have ignored at the begining who shows it …
Abhik35/Assignment-PCA-Data-Mining-Wine-
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
Perform Principal component analysis and perform clustering using first 3 principal component scores (both heirarchial and k mean clustering(scree plot or elbow curve) and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data (class column we have ignored at the begining who shows it …
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published