Puzzle methods for data science applications
Vladimir Jotsov, Pepa Petrova, Evtim Iliev · 2016
Applications have been considered of Puzzle methods as a specific standard for improvement of different SAS Enterprise Miner tools. It is shown how the prognostic models have been improved using the considered original data-driven approaches or algorithms or by using different types of Binding, Pointing and classical constraints. As a result, new types of non-implicative causal relations are revealed. Different modifications of the proposed Puzzle methods have been researched aiming at better control of different types of constraints and elaboration of new, contemporary and more universal evolutionary applications of logical and statistical methods in one system.