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Data Mining offers great opportunities for analyzing data related with several themes, one of the most interesting is the educative environment, which has a lot information about many areas which can be improved. Scholar drop out, it’s one of the biggest problems that education faces, but the great amount of factors that cause it, make it difficult for analyzing. This work presents an analysis of the elementary school drop out problem using techniques like decision tree and generation of association rules for obtaining models that allow to identify the most important family aspects that causes scholar desertion.

Analyzing the Effect of Family Factors over the Scholar drop out at Elementary School using Classification and Association Rules Techniques