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.
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