Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Machine Learning
Feature Extraction, Construction and Selection: A Data Mining Perspective
Feature Extraction, Construction and Selection: A Data Mining Perspective
Machine Learning
Discretization and Grouping: Preprocessing Steps for Data Mining
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
An introduction to variable and feature selection
The Journal of Machine Learning Research
Constructive induction on decision trees
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Improving incremental wrapper-based feature subset selection by using re-ranking
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Fast wrapper feature subset selection in high-dimensional datasets by means of filter re-ranking
Knowledge-Based Systems
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Estimating animal's genetic merit (or breeding value) plays a major role in the Manchego sheep selection scheme (ESROM), started fifteen years ago with the goal of improving Manchego sheep production figures. In the ESROM scheme the breeding value is estimated each semester by using BLUP animal model. In this paper we study the use of data mining techniques to deal with breeding value classification. The purpose of the paper is not to replace the use of BLUP in the ESROM, on the contrary, we intend to learn in a supervised way from the results produced by BLUP, and to use the learned models to provide preliminary information about the breeding value of an animal. We use standard classification techniques combined with feature subset selection in order to identify good (subsets of) predictors. We also show that the classifiers accuracy can be considerably improved by attribute construction.