the vectors/points to be clustered stored as rows of a matrix
stop when the number of clusters equals k
Calculate the centroids based on current assignment of points to clusters.
Given a new point/vector y, determine which cluster it belongs to.
Given a new point/vector y, determine which cluster it belongs to.
the vector to classify
Create initial clusters where each point forms its own cluster.
Create initial clusters where each point forms its own cluster.
the first set
the second set
Iteratively merge clusters until until the number of clusters equals k.
Iteratively merge clusters until until the number of clusters equals k.
Compute a distance metric between vectors/points u and v.
Compute a distance metric between vectors/points u and v.
the first vector/point
the second vector/point
For each data point, determine its cluster assignment.
Show the flaw by printing the error message.
Show the flaw by printing the error message.
the method where the error occurred
the error message
Get the name of the i-th cluster.
Get the name of the i-th cluster.
Create initial clusters where each point forms its own cluster.
Set the names for the clusters.
Cluster several vectors/points using hierarchical clustering. Start with each point forming its own cluster and merge clusters until there are only 'k'.