Prediction of a model for the detection of fraud in e-transactions

The work consisted in the implementation of different classification methods of machine learning already existing, and the development of several scientific papers about classification algorithms which don’t exist already in any of the free libraries of the market; we used the language R with the IDE eclipse.

After we made the choice of the algorithm which gives the best result, the work consisted in its optimization and evaluation, using several techniques of design of algorithms. Like analysis of correctness and time complexity reduction. We used dynamic programming and heuristics.

The third task was its integration with the algorithm of Map Reduce, for its implementation in a computer cluster RHadoop, and its implementation in multi-core programming with the programming language Julia.

After the construction of the model and its implementations we made a critical analysis of performances, we optimized its parameters using the ROC space and finally we made the comparisons with the models of the market using the confusion matrix.

We developed as well an interface in Java J2SE using the libraries Swing, AWT and Prefuse to the visualization of the model and its statistics.

Lille - France, April - September 2013