01618nas a2200241   4500000000100000000000100001008004100002260001200043653001400055653001900069653001400088653001200102100002100114700002000135700002100155700002400176245011000200856009700310300001000407490000600417520093900423022001401362       2013                            d  c03/201310aAI system10aClassification10aEducation10aSchools1 aY Villuendas-Rey1 aC Rey-Benguría1 aY Caballero-Mota1 aM M García-Lorenzo00aImproving the family orientation process in Cuban Special Schools trough Nearest Prototype classification  uhttp://www.ijimai.org/journal/sites/default/files/files/2013/03/ijimai20132_12_pdf_27060.pdf  a12-220 v23 aCuban Schools for children with Affective – Behavioral Maladies (SABM) have as goal to accomplish a major change in children behavior, to insert them effectively into society. One of the key elements in this objective is to give an adequate orientation to the children’s families; due to the family is one of the most important educational contexts in which the children will develop their personality. The family orientation process in SABM involves clustering and classification of mixed type data with non-symmetric similarity functions. To improve this process, this paper includes some novel characteristics in clustering and prototype selection. The proposed approach uses a hierarchical clustering based on compact sets, making it suitable for dealing with non-symmetric similarity functions, as well as with mixed and incomplete data. The proposal obtains very good results on the SABM data, and over repository databases.  a1989-1660