How to calculate the distance of a cluster?
Choose a distance function for clusters – for clusters formed by just one point, D should reduce to d. Start from N clusters, each containing one item. Then, at each iteration: a) using the current matrix of cluster distances, find two closest clusters.
What do you mean by the term clustering?
Until now “clustering” means to me to find a partition of a given cloud of data s.t. a given objective function is minimized. Such objective function is defined by introducing once and for all a distance or “distance-like” function, i.e. a measure of dissimilarity which fails to satisfy all 3 axioms defining a distance on a metric set.
Which is the default distance for hierarchical clustering?
For most common hierarchical clustering software, the default distance measure is the Euclidean distance. This is the square root of the sum of the square differences. However, for gene expression, correlation distance is often used. The distance between two vectors is 0 when they are perfectly correlated.
Why do I get a different clustering sequence?
If you had picked the other pair first, you could get a different clustering sequence. This is typically not a big problem but could be if it happens early on. The only way to see if this has happened, is to shuffle the items and redo the clustering method to see if you get a different result.
When to use dis similarity in clustering method?
There is no definitive answer to your question, as even within the same method the choice of the distance to represent individuals (dis)similarity may yield different result, e.g. when using euclidean vs. squared euclidean in hierarchical clustering.
When to use cluster analysis on a data set?
When using cluster analysis on a data set to group similar cases, one needs to choose among a large number of clustering methods and measures of distance. Sometimes, one choice might influence the other, but there are many possible combinations of methods.