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  • Search: subject:"Misclassification Rate"
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Year of publication
Subject
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Alpha-procedure 3 DD-plot 3 Misclassification rate 3 misclassification rate 3 Accuracy Ratio 2 Clusteranalyse 2 Financial Ratio 2 Misclassification Rate 2 Theorie 2 pattern recognition 2 supervised learning 2 zonoid depth 2 Bandwidth 1 Bayes risk 1 Bayes-Statistik 1 Classification and Regression Tree 1 Classi¯cation and Regression Tree 1 Cross-validation 1 Data depth 1 Deutschland 1 Discriminant Analysis 1 Elliptic symmetry 1 Expected Misclassification Rate 1 Feature selection 1 High Dimensionality 1 High-dimensional classification 1 Kernel density estimation 1 Kreditwürdigkeit 1 Large p 1 Linear discriminant analysis (LDA) 1 Min-Max Regret 1 Multi-scale smoothing 1 Naive Bayes 1 Nichtparametrisches Verfahren 1 Pattern recognition 1 Prognoseverfahren 1 Supervised learning 1 Support vector machine 1 Zonoid depth 1 intersection test 1
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Online availability
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Free 5 Undetermined 4
Type of publication
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Book / Working Paper 5 Article 4
Type of publication (narrower categories)
All
Working Paper 2
Language
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Undetermined 5 English 4
Author
All
Lange, Tatjana 3 Mosler, Karl 3 Mozharovskyi, Pavlo 3 Zhang, Junni L. 2 Bradley, Jonathan 1 Cao, Longbing 1 Dutta, Subhajit 1 Farnsworth, David 1 Ghosh, Anil 1 Härdle, Wolfgang 1 Härdle, Wolfgang Karl 1 Miao, Baiqi 1 Silva, Pedro Duarte 1 Wang, Cheng 1
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Institution
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Faculdade de Economia e Gestão, Universidade Católica Portuguesa 1 Seminar für Wirtschafts- und Sozialstatistik, Wirtschafts- und Sozialwissenschaftliche Fakultät 1 Sonderforschungsbereich 649: Ökonomisches Risiko, Wirtschaftswissenschaftliche Fakultät 1
Published in...
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Annals of the Institute of Statistical Mathematics 1 Computational Statistics & Data Analysis 1 Discussion Papers in Econometrics and Statistics 1 Discussion Papers in Statistics and Econometrics 1 Journal of Applied Statistics 1 SFB 649 Discussion Paper 1 SFB 649 Discussion Papers 1 Statistical Papers / Springer 1 Working Papers de Gestão (Management Working Papers) 1
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Source
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RePEc 7 EconStor 2
Showing 1 - 9 of 9
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Fast nonparametric classification based on data depth
Lange, Tatjana; Mosler, Karl; Mozharovskyi, Pavlo - 2012
A new procedure, called DD-procedure, is developed to solve the problem of classifying d-dimensional objects into q Ï 2 classes. The procedure is completely nonparametric; it uses q-dimensional depth plots and a very efficient algorithm for discrimination analysis in the depth space [0, 1]q ....
Persistent link: https://www.econbiz.de/10010311009
Saved in:
Cover Image
Fast nonparametric classification based on data depth
Lange, Tatjana; Mosler, Karl; Mozharovskyi, Pavlo - Seminar für Wirtschafts- und Sozialstatistik, … - 2012
A new procedure, called DD-procedure, is developed to solve the problem of classifying d-dimensional objects into q Ï 2 classes. The procedure is completely nonparametric; it uses q-dimensional depth plots and a very efficient algorithm for discrimination analysis in the depth space [0, 1]q ....
Persistent link: https://www.econbiz.de/10010986596
Saved in:
Cover Image
LINEAR DISCRIMINANT RULES for HIGH-DIMENSIONAL CORRELATED DATA: ASYMPTOTIC and FINITE SAMPLE RESULTS
Silva, Pedro Duarte - Faculdade de Economia e Gestão, Universidade Católica … - 2009
A new class of linear discrimination rules, designed for problems with many correlated variables, is proposed. This proposal tries to incorporate the most important patterns revealed by the empirical correlations and accurately approximate the optimal Bayes rule as the number of variables...
Persistent link: https://www.econbiz.de/10005012079
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The bayesian additive classification tree applied to credit risk modelling
Zhang, Junni L.; Härdle, Wolfgang Karl - 2008
We propose a new nonlinear classification method based on a Bayesian sum-of-trees model, the Bayesian Additive Classification Tree (BACT), which extends the Bayesian Additive Regression Tree (BART) method into the classification context. Like BART, the BACT is a Bayesian nonparametric additive...
Persistent link: https://www.econbiz.de/10010274137
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The Bayesian Additive Classification Tree Applied to Credit Risk Modelling
Zhang, Junni L.; Härdle, Wolfgang - Sonderforschungsbereich 649: Ökonomisches Risiko, … - 2008
We propose a new nonlinear classification method based on a Bayesian "sum-of-trees" model, the Bayesian Additive Classification Tree (BACT), which extends the Bayesian Additive Regression Tree (BART) method into the classi- fication context. Like BART, the BACT is a Bayesian nonparametric...
Persistent link: https://www.econbiz.de/10005678032
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Fast nonparametric classification based on data depth
Lange, Tatjana; Mosler, Karl; Mozharovskyi, Pavlo - In: Statistical Papers 55 (2014) 1, pp. 49-69
A new procedure, called D D α-procedure, is developed to solve the problem of classifying d-dimensional objects into q ≥ 2 classes. The procedure is nonparametric; it uses q-dimensional depth plots and a very efficient algorithm for discrimination analysis in the depth space [0,1]<Superscript> q </Superscript>....</superscript>
Persistent link: https://www.econbiz.de/10010998619
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Optimal feature selection for sparse linear discriminant analysis and its applications in gene expression data
Wang, Cheng; Cao, Longbing; Miao, Baiqi - In: Computational Statistics & Data Analysis 66 (2013) C, pp. 140-149
a better result with a reduced misclassification rate. …
Persistent link: https://www.econbiz.de/10010871430
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On robust classification using projection depth
Dutta, Subhajit; Ghosh, Anil - In: Annals of the Institute of Statistical Mathematics 64 (2012) 3, pp. 657-676
Persistent link: https://www.econbiz.de/10010848674
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Testing for Mutual Exclusivity
Bradley, Jonathan; Farnsworth, David - In: Journal of Applied Statistics 36 (2009) 11, pp. 1307-1314
A test for two events being mutually exclusive is presented for the case in which there are known rates of misclassification of the events. The test can be utilized in other situations, such as to test whether a set is a subset of another set. In the test, the null value of the probability of...
Persistent link: https://www.econbiz.de/10009225474
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