A Data Analysis workbench. It uses predictive techniques for anomaly detetion.
Technologies and algorithms used: ML framework : WEKA api. UI : Sample code from IBM Bluemix examples, Bootstrap, nvd3 for Cluster visualization. Server side: Plain Java servlets that returns JSON output. Apache tomcat, MySQL
Algorithms used from WEKA Outlier report : Local Outlier Factor algorithm Clustering : K-means Data Patterns and Test Data Prediction: C4.5