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Toplam kayıt 15, listelenen: 1-10
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 ...
Omnivariate rule induction using a novel pairwise statistical test
(IEEE Computer Soc, 2013-09)
Rule learning algorithms, for example, RIPPER, induces univariate rules, that is, a propositional condition in a rule uses only one feature. In this paper, we propose an omnivariate induction of rules where under each ...
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 ...
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 ...
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 ...
WikiLeaks on the Middle East: Obscure diplomacy networks and binding spaces
(Routledge Journals, 2014-10-02)
In this paper, we explore the flow of information regarding strategic Middle Eastern countries in the WikiLeaks 'diplomatic cables' by applying data-mining techniques to construct directed networks. The results show that ...
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 ...
Design and analysis of classifier learning experiments in bioinformatics: survey and case studies
(IEEE Computer Soc, 2012-12)
In many bioinformatics applications, it is important to assess and compare the performances of algorithms trained from data, to be able to draw conclusions unaffected by chance and are therefore significant. Both the design ...
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 ...
Tree Ensembles on the induced discrete space
(Institute of Electrical and Electronics Engineers Inc., 2016-05)
Decision trees are widely used predictive models in machine learning. Recently, K-tree is proposed, where the original discrete feature space is expanded by generating all orderings of values of k discrete attributes and ...