P. Brazdil, J. Gama, and B. Henery, Comparison of ML and statistical approaches using meta level learning. Workshop Notes on Real-World Applications of Machine Learning, European Conference on Machine Learning. Home/Search Document Not in Database Summary Related Articles Check |
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A Benchmark for Classifier Learning - Zheng (1993) (5 citations) (Correct)
....is as accurate as the rules created by the majority of machine learning systems. Thrun et al. 1991] use the MONK s problems to evaluate 19 symbolic and non symbolic learning algorithms. To the best of our knowledge, however, there is no generally accepted benchmark for classifier learning. Brazdil et al. 1993] use twenty three domains from the Esprit Project StatLog to compare and characterize twenty two different learning algorithms by using meta level learning. The test results of the algorithms on the domains together with domain descriptions are used as input data for the meta level learning and, ....
P. Brazdil, J. Gama, and B. Henery, Comparison of ML and statistical approaches using meta level learning, Workshop Notes on RealWorld Applications of Machine Learning, European Conference on Machine Learning, 1993.
MLC++: A Machine Learning Library in C++ - Kohavi, John, Long, Manley.. (1994) (14 citations) (Correct)
....The data generator should be extended to allow generating non discrete data, to incorporate different noise models, and varying distributions. Hybrid approaches Hybrid algorithms of different kinds can be tested. One of the more intriguing things we wish to do is meta level learning [BGH94, BaGH93] i.e. to have a machine learning algorithm induce rules that will define (empirically) when an algorithm is applicable, or which algorithm should be used for a given dataset, and with what parameterization. We believe that only through projects like MLC and [TMS94] can we reach such a ....
Pavel Brazdil, Jo ao Gama, and Bob Henery. Comparisons of ML and statistical approaches using meta level learning. In Proceedings of the ECML93 workshop on Real-World Applications of Machine Learning. Springer, 1993.
Constructing New Attributes for Decision Tree Learning - Zheng (1996) (3 citations) (Correct)
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P. Brazdil, J. Gama, and B. Henery, Comparison of ML and statistical approaches using meta level learning. Workshop Notes on Real-World Applications of Machine Learning, European Conference on Machine Learning.
A Benchmark for Classifier Learning - Zheng (1993) (5 citations) (Correct)
No context found.
P. Brazdil, J. Gama, and B. Henery, Comparison of ML and statistical approaches using meta level learning, Workshop Notes on Real-World Applications of Machine Learning, ECML, (1993).
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