  Table (database) / Relational database Classification for big/smart/fast data
machine learning is one of the most important tasks of predictive analytics and
extracting valuable information from data. It is core applied technique for
what now understood under data science and/or artificial intelligence. Widely
used Decision Tree (Random Forest) and rare used rule based PRISM , VFST, etc
classifiers are empirical substitutions of theoretically correct to use Boolean
functions minimization. Developing Minimization of Boolean functions algorithms
is started long time ago by Edward Veitch's 1952. Since it, big efforts by wide
scientific/industrial community was done to find feasible solution of Boolean
functions minimization. In this paper we propose consider table data
classification from mathematical point of view, as minimization of Boolean
functions. It is shown that data representation may be transformed to Boolean
functions form and how to use known algorithms. For simplicity, binary output
function is used for development, what opens doors for multivalued outputs
developments.
