CTC datasets consist of a mix of preprocessed network traffic data with and without covert timing channels. They are a demanding challenge for machine learning and data mining algorithms.
MDCGen is a tool for generating multidimensional synthetic datasets. It is devised for testing, evaluating and benchmarking clustering algorithms.
ODTF (One-class Decision Tree Fuzzyfier) is an algorithm that wraps a linear DT and establishes class-membership scores based on weighted distances to decision thresholds.
GOI provides a set of indices for absolute cluster validation and for the interpretation of the dataset context based on geometrical properties of the multidimensional data.
SDO (Sparse Data Observers) is an algorithm that establihes distance-based outlierness scores on data samples. SDO is devised to be embedded in systems or frameworks that operate autonomously and must process large amounts of data in a continuos manner. SDO is a machine learning solution for Big Data and stream data applications.