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So we are back. PASS SQL Saturday is coming to Slovenia again on December 12th, 2015. Remember last two years? We had two great events. According to feedback, everybody was satisfied and happy. Let's make another outstanding event! How can you help?
First of all, these events are free for attendees. Of course, this is possible only because ...

Support vector machines are both, unsupervised and supervised learning models for classification and regression analysis (supervised) and for anomaly detection (unsupervised). Given a set of training examples, each marked as belonging to one of categories, an SVM training algorithm builds a model that assigns new examples into one category. An SVM ...

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 ...

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 ...

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 ...

Back home from SQLBits XII, back to normal life. However, I am already missing the conference. I have spoken with quite a few other speakers, and our conclusion is, as my friend Niko Neugebauer said: this conference is simply second to none. Great content, and very interesting split into three days: seminars if you wish to get more personal touch ...

This is the fifth, the final part of the fraud detection whitepaper. You can find the first part, the second part, the third part, and the fourth part in my previous blog posts about this topic. The Results In my original fraud detection whitepaper I wrote for SolidQ, I was advised by my friends to include some concrete and simple numbers to ...

This is the fourth part of the fraud detection whitepaper. You can find the first part, the second part, and the third part in my previous blog posts about this topic. Data Mining Models We create multiple mining models by using different algorithms, different input data sets, and different algorithm parameters. Then we evaluate the models in ...

While working on different fraud detection projects, I developed my own approach to the solution for this problem. In my PASS Summit 2013 session I am introducing this approach. I also wrote a whitepaper on the same topic, which was generously reviewed by my friend Matija Lah. In order to spread this knowledge faster, I am starting a series of ...



