Artículo
Data Set Editing by Ordered Projection
Autor/es | Aguilar, Jesús S.
Riquelme Santos, José Cristóbal Toro Bonilla, Miguel |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2001 |
Fecha de depósito | 2020-08-07 |
Publicado en |
|
Resumen | This paper presents a new approach to data set editing. The algorithm (EOP: Editing by Ordered Projection) has
some interesting characteristics: important reduction of the number of examples from the database; lower ... This paper presents a new approach to data set editing. The algorithm (EOP: Editing by Ordered Projection) has some interesting characteristics: important reduction of the number of examples from the database; lower computational cost (O(mn log n)) with respect to other typical algorithms due to the absence of distance calculations; conservation of the decision boundaries, especially from the point of view of the application of axis-parallel classifiers. The performance of EOP is analysed in two ways: percentage of reduction and classification. EOP has been compared to IB2, ENN and SHRINK concerning the percentage of reduction and the computational cost. In addition, we have analysed the accuracy of k-NN and C4.5 after applying the reduction techniques. An extensive empirical study using databases with continuous attributes from the UCI repository shows that EOP is a valuable preprocessing method for the later application of any axis-parallel learning algorithm. |
Agencias financiadoras | Comisión Interministerial de Ciencia y Tecnología (CICYT). España |
Identificador del proyecto | TIC2001-1143-C03-02 |
Cita | Aguilar, J.S., Riquelme Santos, J.C. y Toro Bonilla, M. (2001). Data Set Editing by Ordered Projection. Intelligent Data Analysis, 5 (5), 405-417. |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
Data Set Editing by Ordered ... | 219.6Kb | [PDF] | Ver/ | |