Published

2012-05-01

COMPARACIÓN ENTRE SVM Y REGRESIÓN LOGÍSTICA: ¿CUÁL ES MÁS RECOMENDABLE PARA DISCRIMINAR?

COMPARISON BETWEEN SVM AND LOGISTIC REGRESSION: WHICH ONE IS BETTER TO DISCRIMINATE?

Keywords:

clasificación, genética, máquinas de soporte vectorial, regresión logística, simulación (es)
Classification, Genetics, Logistic regression, Simulation, Support vector machines (en)

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Authors

  • Diego Alejandro Salazar Universidad Nacional de Colombia Sede Medellín
  • Jorge Iván Vélez Universidad Nacional de Colombia Sede Medellín
  • Juan Carlos Salazar Universidad Nacional de Colombia Sede Medellín
La clasificación de individuos es un problema muy común en el trabajo estadístico aplicado. Si X es un conjunto de datos de una población en la que sus elementos pertenecen a g clases, el objetivo de los métodos de clasificación es determinar a cuál de ellas pertenecerá una nueva observación. Cuando g = 2, uno de los métodos más utilizados es la regresión logística. Recientemente, las Máquinas de Soporte Vectorial se han convertido en una alternativa importante. En este trabajo se exponen los principios básicos de ambos métodos y se da respuesta a la pregunta de cuál es más recomendable para discriminar, vía simulación. Finalmente, se presenta una aplicación con datos provenientes de un experimento con microarreglos.
The classification of individuals is a common problem in applied statistics. If X is a data set corresponding to a sample from an specific population in which observations belong to g different categories, the goal of classification methods is to determine to which of them a new observation will belong to. When g = 2, logistic regression (LR) is one of the most widely used classification methods. More recently, Support Vector Machines (SVM) has become an important alternative. In this paper, the fundamentals of LR and SVM are described, and the question of which one is better to discriminate is addressed using statistical simulation. An application with real data from a microarray experiment is presented as illustration.

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Copyright (c) 2012 Revista Colombiana de Estadística

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