Gain in-depth insights with jBEAM data mining

Special data mining algorithms deliver the final step in a complete Big Test Data analysis: with their help, users can discover correlations that would otherwise be difficult to track. As an open framework (ASAM-CEA), jBEAM allows users to develop data mining algorithms or add new methods (libraries: Java, MATLAB). All data mining results can also be visualized with the graphic objects available in jBEAM.

These approaches and algorithms are already implemented in jBEAM:

• Pattern: Apriori, FPGrows, etc.
• Clustering: K-Means, Optics, DBScan, etc.
• Prediction: Linear and Periodic Prediction, Support Vector Machine (SVM) etc.
• Transformation: Principal Component Analysis (PCA), etc.