Abstract
In this paper we describe an ESPRIT project known as ‘Stat-Log’ whose purpose is the comparison of learning algorithms. We give a brief summary of some of the algorithms in the project: linear and quadratic discriminant analysis, k nearest neighbour, CART, backpropagation, SMART, ALLOC80 and Pearl's polytree algorithm. We discuss the results obtained for two datasets, one of handwritten digits and the other of vehicle silhouettes.
This work has been supported by the Commission of the European Communities under ESPRIT project no 5170: Comparative Testing of Statistical and Logical Learning, Statlog.
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© 1993 Springer-Verlag
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Sutherland, A., Henery, R., Molina, R., Taylor, C.C., King, R. (1993). Statistical methods in learning. In: Bouchon-Meunier, B., Valverde, L., Yager, R.R. (eds) IPMU '92—Advanced Methods in Artificial Intelligence. IPMU 1992. Lecture Notes in Computer Science, vol 682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56735-6_54
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DOI: https://doi.org/10.1007/3-540-56735-6_54
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