Abstract
In recent years there has been some interest in using machine learning techniques as part of pattern recognition systems. However, little attention is typically given to the validity of the features and types of rules generated by these systems and how well they perform across a variety of features and patterns. A comparison of the classification performance of two different types of decision tree techniques and their associated feature types is presented.
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© 1997 Springer-Verlag
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Lam, C.P., West, G.A.W., Caelli, T.M. (1997). Data representations and machine learning techniques. In: Liu, X., Cohen, P., Berthold, M. (eds) Advances in Intelligent Data Analysis Reasoning about Data. IDA 1997. Lecture Notes in Computer Science, vol 1280. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0052838
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DOI: https://doi.org/10.1007/BFb0052838
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