Improving the family orientation process in Cuban Special Schools trough Nearest Prototype classification

Abstract

-Cuban Schools for children with AffectiveBehavioral 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.

Simultaneous instance and feature selection for improving prediction in special education data

“…In addition, the deterministic algorithm for instance and feature selection proposed by Dassarathy and Sánchez (DS) was considered in the comparison (Dasarathy and Sánchez Garreta, 2000). The proposal was also compared to the PS algorithm (Villuendas-Rey, Rey-Benguría, Caballero-Mota and García-Lorenzo, 2013) proposed for preprocessing the SABM. Table VIII shows the configuration of parameters for the algorithms, as suggested in the corresponding papers.…”

“…To our knowledge, no works regarding diagnosis of Cuban children with affectivebehavioral disorders using automatic learning tool exist apart from the work by Villuendas-Rey, Garcia-Lorenzo and Bello (2013) and Villuendas-Rey, Rey-Benguría, Caballero-Mota and García-Lorenzo (2013).…”

“…Although the work done by Villuendas-Rey et al in family orientation for the SABM system results in the correct classification of the families, it only considers instance selection to preprocess the SABM data (Villuendas-Rey, Rey-Benguría, Caballero-Mota and García-Lorenzo, 2013). This paper explores using a new combined instance and feature selection technique to select relevant instances and features, leading to better classification, and to a simplification of the SABM data set.…”

Legal Issues Concerning P2P Exchange of Educational Materials and Their Impact on E-Learning Multi-Agent Systems

“…Every student is encouraged to keep a repository of downloaded educational materials, such as books, shorter documents, databases, images, videos, audio files, etc… in which the copyright issues can be legally certified [12]. We think that if the tools provided are used to search and bring back that material for everywhere on the Internet, the students would agree to a reasonable degree of control on legal materials.…”

Prediction of High Capabilities in the Development of Kindergarten Children

“…The Nearest Neighbor (NN) classifier [12] is one of the simplest yet accurate algorithms for non-parametric prediction, and its ability of returning the neighbors of an unclassified pattern makes it very suitable for soft sciences prediction problems. The NN classifier had been used previously to successfully solve educational problems in Cuba, such as family classification [13].…”