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With the KMeans algorithm, each object is assigned to exactly one cluster. It is assigned to this cluster with a probability equal to 1.0. It is assigned to all other clusters with a probability equal to 0.0. This is hard clustering.
Instead of distance, you can use a probabilistic measure to determine cluster membership. For example, you can ...

Hierarchical clustering could be very useful because it is easy to see the optimal number of clusters in a dendrogram and because the dendrogram visualizes the clusters and the process of building of that clusters. However, hierarchical methods don’t scale well. Just imagine how cluttered a dendrogram would be if 10,000 cases would be shown on ...

Hierarchical clustering can use any kind of a distance; in fact, it does not need the original cases once the distance matrix is built. Therefore, you can use a distance that takes into account correlations, like the Mahalanobis distance (http://en.wikipedia.org/wiki/Mahalanobis_distance).
MS supports KMeans and ExpectationMaximization ...

Clustering is the process of grouping the data into classes or clusters so that objects within a cluster have high similarity in comparison to one another, but are very dissimilar to objects in other clusters. Dissimilarities are assessed based on the attribute values describing the objects.
There are a large number of clustering algorithms. The ...

Kevin,
First of all, thank you for your kind comment.
In SQL, you typically search for distinct combinations of items in the same transaction with either join or apply operator. I prefer apply. Bellow is an example that finds itemsets of size 1, 2, and 3. However, I would not recommend doing this in SQL  why would you reinvent the wheel? You ...

The Association Rules algorithm is specifically designed for use in market basket analyses. This knowledge can additionally help in identifying crossselling opportunities and in arranging attractive packages of products. This is the most popular algorithm used in web sales. You can even include additional discrete input variables and predict ...

When I click the link from the post, it drives me directly to the 2014 guide and opens a PDF. Are you using the same link?

And we started in Vienna:)

In two days, I am starting my first conference trip for this year. Therefore, it seems to me it is high time to write down my plan for the first semester of this year. Of course, I m adding my food plan for each event:) SQL Saturday #374 Vienna. On Friday, February 27th, I am having a fullday seminar “Advanced Data Modeling Topics” in ...
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