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Toplam kayıt 18, listelenen: 11-18
Model selection in omnivariate decision trees using Structural Risk Minimization
(Elsevier Science Inc, 2011-12-01)
As opposed to trees that use a single type of decision node, an omnivariate decision tree contains nodes of different types. We propose to use Structural Risk Minimization (SRM) to choose between node types in omnivariate ...
A novel kernel to predict software defectiveness
(Elsevier Science Inc, 2016-09)
Although the software defect prediction problem has been researched for a long time, the results achieved are not so bright. In this paper, we propose to use novel kernels for defect prediction that are based on the ...
Quadratic programming for class ordering in rule induction
(Elsevier Science BV, 2015-03-01)
Separate-and-conquer type rule induction algorithms such as Ripper, solve a K>2 class problem by converting it into a sequence of K - 1 two-class problems. As a usual heuristic, the classes are fed into the algorithm in ...
Univariate decision tree induction using maximum margin classification
(Oxford Univ Press, 2012-03)
In many pattern recognition applications, first decision trees are used due to their simplicity and easily interpretable nature. In this paper, we propose a new decision tree learning algorithm called univariate margin ...
Cryptanalysis of Fridrich's chaotic image encryption
(World Scientific Publishing, 2010-05)
We cryptanalyze Fridrich's chaotic image encryption algorithm. We show that the algebraic weaknesses of the algorithm make it vulnerable against chosen-ciphertext attacks. We propose an attack that reveals the secret ...
On the feature extraction in discrete space
(Elsevier Sci Ltd, 2014-05)
In many pattern recognition applications, feature space expansion is a key step for improving the performance of the classifier. In this paper, we (i) expand the discrete feature space by generating all orderings of values ...
Software defect prediction using Bayesian networks
(Springer, 2014-02)
There are lots of different software metrics discovered and used for defect prediction in the literature. Instead of dealing with so many metrics, it would be practical and easy if we could determine the set of metrics ...
Mapping classifiers and datasets
(Pergamon-Elsevier Science Ltd, 2011-04)
Given the posterior probability estimates of 14 classifiers on 38 datasets, we plot two-dimensional maps of classifiers and datasets using principal component analysis (PCA) and Isomap. The similarity between classifiers ...