Applying support vector machines and mutual information to book losses prediction

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@InProceedings{Mora:2010:ijcnn,

• author = "A. M. Mora and L. J. Herrera and J. Urquiza and I. Rojas and J. J. Merelo",
• title = "Applying support vector machines and mutual information to book losses prediction",
• booktitle = "International Joint Conference on Neural Networks (IJCNN 2010)",
• year = "2010",
• address = "Barcelona, Spain",
• month = "18-23 " # jul,
• publisher = "IEEE Press",
• keywords = "genetic algorithms, genetic programming, SVM",
• isbn13 = "978-1-4244-6917-8",
• DOI = "doi:10.1109/IJCNN.2010.5596710",
• size = "7 pages",
• abstract = "This work presents a feasible solution to the problem of book losses prediction from financial and general data in companies. The specific problem tackled in this work corresponds to a real dataset of Spanish companies. A Mutual Information-based criterion has been applied in order to reduce the initial set of variables, and a Support Vector Machine classifier has been designed to perform the prediction. The results show that the proposed approach obtains an important reduction of the number of variables needed to perform the prediction, improving the generalisation capabilities of the model. The accuracy rates were above the 84percent in the test set, much better than those obtained by other soft-computing algorithms (such as Genetic Programming, Self-Organising Maps or Artificial Neural Networks) working with the same dataset and presented in previous works. The proposed approach shows to be promising and could be determinant in providing the experts with the right tools for the selection of the relevant factors and for the prediction in this difficult problem.",
• notes = "WCCI 2010. Also known as \cite{5596710}",

}

Genetic Programming entries for Antonio M Mora Garcia Luis Javier Herrera Maldonado Jose Miguel Urquiza Ortiz Ignacio Rojas Ruiz Juan Julian Merelo

Citations