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Anticipating the political behavior of people will be considerable help forelection candidates to assess the possibility of their success and to beacknowledged about the public motivations to select them. In this paper, weprovide a general schematic of the architecture of participation anticipatingsystem in presidential election by using KNN, Classification Tree and Na\"iveBayes and tools orange based on crisp which had hopeful output. To test andassess the proposed model, we begin to use the case study by selecting 100qualified persons who attend in 11th presidential election of Islamic republicof Iran and anticipate their participation in Kohkiloye & Boyerahmad. Weindicate that KNN can perform anticipation and classification processes withhigh accuracy in compared with two other algorithms to anticipateparticipation.

Participation anticipating in elections using data mining methods