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Regularized principal components of heritability

Fang, Yixin; Feng, Yang; Yuan, Ming - In: Computational Statistics 29 (2014) 3, pp. 455-465

In family studies with multiple continuous phenotypes, heritability can be conveniently evaluated through the so-called principal-component of heredity (PCH, for short; Ott and Rabinowitz in Hum Hered 49:106–111, <CitationRef CitationID="CR12">1999</CitationRef>). Estimation of the PCH, however, is notoriously difficult when entertaining...</citationref>

Persistent link: https://www.econbiz.de/10010998518

PLS and dimension reduction for classification

Liu, Yushu; Rayens, William - In: Computational Statistics 22 (2007) 2, pp. 189-208

Persistent link: https://www.econbiz.de/10005166780

PLS classification of functional data

Preda, Cristian; Saporta, Gilbert; Lévéder, Caroline - In: Computational Statistics 22 (2007) 2, pp. 223-235

Persistent link: https://www.econbiz.de/10005613191

GA-Ensemble: a genetic algorithm for robust ensembles

Oh, Dong-Yop; Gray, J. - In: Computational Statistics 28 (2013) 5, pp. 2333-2347

Many simple and complex methods have been developed to solve the classification problem. Boosting is one of the best …. In this article we propose a new method, GA-Ensemble, which directly solves for the set of weak classifiers and their … set error rates of GA-Ensemble, AdaBoost, and GentleBoost (an outlier-resistant version of AdaBoost) using several …

Persistent link: https://www.econbiz.de/10010998475

Music and timbre segmentation by recursive constrained K-means clustering

Krey, Sebastian; Ligges, Uwe; Leisch, Friedrich - In: Computational Statistics 29 (2014) 1, pp. 37-50

Clustering of features generated of musical sound recordings proved to be beneficial for further classification tasks …

Persistent link: https://www.econbiz.de/10010998531

Partial least squares classification for high dimensional data using the PCOUT algorithm

Turkmen, Asuman; Billor, Nedret - In: Computational Statistics 28 (2013) 2, pp. 771-788

Classification of samples into two or multi-classes is to interest of scientists in almost every field. Traditional … statistical methodology for classification does not work well when there are more variables (p) than there are samples (n) and it … is highly sensitive to outlying observations. In this study, a robust partial least squares based classification method …

Persistent link: https://www.econbiz.de/10010998538

Interactive visualization in multiclass learning: integrating the SASSC algorithm with KLIMT

Conversano, Claudio - In: Computational Statistics 26 (2011) 4, pp. 711-731

Persistent link: https://www.econbiz.de/10009400164

Multinomial event naive Bayesian modeling for SAGE data classification

Jin, Xin; Zhou, Wengang; Bie, Rongfang - In: Computational Statistics 22 (2007) 1, pp. 133-143

Persistent link: https://www.econbiz.de/10005166790

Iterative Denoising

Giles, Kendall; Trosset, Michael; Marchette, David; … - In: Computational Statistics 23 (2008) 4, pp. 497-517

Persistent link: https://www.econbiz.de/10005613154

Feature clustering for instrument classification

Ligges, Uwe; Krey, Sebastian - In: Computational Statistics 26 (2011) 2, pp. 279-291

Persistent link: https://www.econbiz.de/10009149754