Autonomous Clustering for Machine Learning

In this paper, starting from a collection of training examples, we show how to produce a very compact set of classification rules. The induction idea is a clustering principle based on Kohonen’s self-organizing algorithms. The function to optimize in the aggregation of examples to become rules is a classificatory quality measure called impurity level, which was previously employed in our system called Fan. The rule conditions obtained in this way are densely populated areas in the attribute space. The main goal of our system, in addition to its accuracy, is the high quality of explanations that it can provide attached to the classification decisions.

[1]  José Ranilla,et al.  Self-Organizing Symbolic Learned Rules , 1997, IWANN.

[2]  Steven L. Salzberg,et al.  Learning with Nested Generalized Exemplars , 1990 .

[3]  Simon Kasif,et al.  A System for Induction of Oblique Decision Trees , 1994, J. Artif. Intell. Res..

[4]  Aiko M. Hormann,et al.  Programs for Machine Learning. Part I , 1962, Inf. Control..

[5]  Joan Cabestany,et al.  Biological and Artificial Computation: From Neuroscience to Technology , 1997, Lecture Notes in Computer Science.

[6]  Catherine Blake,et al.  UCI Repository of machine learning databases , 1998 .

[7]  David Aha.  A study of instance-based algorithms for supervised learning tasks: mathematica:l , 1990 .

[8]  Nils J. Nilsson,et al.  MLC++, A Machine Learning Library in C++. , 1995 .

[9]  José Ranilla,et al.  Self-Organizing Cases to Find Paradigms , 1999, IWANN.

[10]  José Ranilla,et al.  Machine Learning Usefulness Relies on Accuracy and Self-Maintenance , 1998, IEA/AIE.

[11]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[12]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[13]  Angel P. del Pobil,et al.  Tasks and Methods in Applied Artificial Intelligence , 1998, Lecture Notes in Computer Science.

[14]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[15]  Antonio Bahamonde Rionda,et al.  El nivel de impureza de una regla de clasificación aprendida a partir de ejemplos , 1997 .

[16]  Patrick Brézillon,et al.  Lecture Notes in Artificial Intelligence , 1999 .

[17]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .