

Browse by Tags
All Tags » Data Mining (RSS)
Showing page 1 of 2 (17 total posts)

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 ...

Principal component analysis (PCA) is a technique used to emphasize the majority of the variation and bring out strong patterns in a dataset. It is often used to make data easy to explore and visualize. It is closely connected to eigenvectors and eigenvalues.
A short definition of the algorithm: PCA uses an orthogonal transformation to convert ...

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 ...

Data mining is the most advanced part of business intelligence. With statistical and other mathematical algorithms, you can automatically discover patterns and rules in your data that are hard to notice with online analytical processing and reporting. However, you need to thoroughly understand how the data mining algorithms work in order to ...

It is hard to imagine searching for something on the Web without modern search engines like Bing or Google. However, most contemporary applications still limit users to exact searches only. For end users, even the standard SQL LIKE operator is not powerful enough for approximate searches. In addition, many documents are stored in modern databases; ...

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 ...

More than one year ago, I and Alberto started recording videos for Project Botticelli, and now we have a set of videos about DAX that you can watch online. There are a few videos free, and others are available in the monthly subscription. If you are interested, use this 20% discount code before the end of the December 2013: SQLBI20HOLS2013
The ...

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 ...
1



