Parallelization of data mining algorithms for multicore processors

The article describes a approach of parallel data mining algorithms to be executed on multicore processors of various architecture. The suggested method presents an algorithm as a consequence of pure functions with unified interfaces. For parallel execution additional functions are introduced to share data and models between the parallel threads. Besides such functions allow to obtain various parallel algorithm structures and implement various strategies of execution for different environment conditions. Application of the described method is illustrated through algorithm Naive Bayes.