An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
—Text classification is a widely studied topic in the area of machine learning. A number of techniques have been developed to represent and classify text documents. Most of the t...
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
In many real-world classification problems the input contains a large number of potentially irrelevant features. This paper proposes a new Bayesian framework for determining the r...
Yuan (Alan) Qi, Thomas P. Minka, Rosalind W. Picar...
Classification has been commonly used in many data mining projects in the financial service industry. For instance, to predict collectability of accounts receivable, a binary clas...