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What I am trying to show here is that you essentially have a while-loop that uses the stack to check the end condition.
Generally, clustering validation statistics can be categorized into 3 classes In this chapter, we start by describing the different methods for clustering validation.
The silhouette plot displays a measure of how close each point in one cluster is to points in the neighboring clusters.
For each observation If the data set contains compact and well-separated clusters, the diameter of the clusters is expected to be small and the distance between the clusters is expected to be large. The aim is to compare the identified clusters (by k-means, pam or hierarchical clustering) to an external reference.
We also discuss the different user input validation techniques and cover how to use the Error Provider component to display error messages.
When an application encounters an unexpected situation such as a missing file or input parameter, or a logical error such as performing a division by zero, the application generates exceptions.