M. Minksy and S. Papert. Perceptrons: An Introduction to Computation Geometry. MIT Press, Cambridge, MA, 1969.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....that search for effective and efficient meta classifiers. 5.1 Experimental setting Learning algorithms Five inductive learning algorithms are used in our experiments, Bayes, C4.5, ID3, CART and Ripper. ID3, its successor C4.5 [34] and CART are decision tree based algorithms, Bayes, described in [24], is a naive Bayesian classifier, and Ripper [9] is a rule induction algorithm. Learning tasks Two data sets of real credit card transactions were used in our experiments. The credit card data sets were provided by the Chase and First Union Banks, members of FSTC (Financial Services Technology ....

M. Minksy and S. Papert. Perceptrons: An Introduction to Computation Geometry. MIT Press, Cambridge, MA, 1969.

....sites (each site getting two months of data) and we prepared the set of base classifiers the pruning algorithm is called to evaluate. We obtained these classifiers by applying 5 learning algorithms (three decision tree algorithms, ID3, its successor C4.5, and Cart [3] a naive Bayesian algorithm [18], and the rule induction algorithm Ripper [9] on each month of data, therefore creating 60 base classifiers (10 classifiers per data site) Next, we had each site import the remote base classifiers (50 in total) and used only these in the pruning and meta learning phases thus ensuring that no ....

M. Minksy and S. Papert. Perceptrons: An Introduction to Computation Geometry. MIT Press, (Expanded edition, 1988).

....sites (each site getting two months of data) and we prepared the set of base classifiers the pruning algorithm is called to evaluate. We obtained these classifiers by applying 5 learning algorithms (three decision tree algorithms, ID3, its successor C4.5, and Cart [3] a naive Bayesian algorithm [18], and the rule induction algorithm Ripper [9] on each month of data, therefore creating 60 base classifiers (10 classifiers per data site) Next, we had each site import the remote base classifiers (50 in total) and used only these in the pruning and meta learning phases thus ensuring that no ....

M. Minksy and S. Papert. Perceptrons: An Introduction to Computation Geometry. MIT Press, (Expanded edition, 1988).

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Minksy, M. and Papert, S. (1969). Perceptrons: An Introduction to Computation Geometry.

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