Cluster Analysis (with R)

Input File (.csv only):
Read File

Condition(s) for Subset:
None = > >= < <= != Categorical Variable
None = > >= < <= != Categorical Variable
None = > >= < <= != Categorical Variable
None = > >= < <= != Categorical Variable

Selected Variable(s):
None

Type of Clustering:
Partitioning Clustering using K-means (with number of clusters = 2 3 4 5 6 7 8 9 10 ), maximum number of iterations = , method = Hartigan-Wong Lloyd Forgy MacQueen )
Partitioning Clustering using K-medoids (with number of clusters = 2 3 4 5 6 7 8 9 10 )
Partitioning Clustering using DBSCAN (with reachability distance = ), reachability minimum number of points = )
Hierarchical Clustering using Dendrogram (with method = ward.D2 ward.D single complete average mcquitty median centroid on a sample of size 100 75 50 25 10 5 1 %)
Elbow Method using K-means (with method = silhouette wss gap_stat )



Code:

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