Principal differential analysis for detection of bilabial closure gestures from articulatory data

Sattar, F.; Rudzicz, Frank

doi:10.1016/j.csl.2015.07.002

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“…For the PDA based classification methods, Reimer and Rudzicz (2010) proposed a PDA classifier based on RSQ, and Sattar and Rudzicz (2016) extended the approach by using a support vector machine. Dalla et al (2014) compared quadratic discriminant analysis with PDA components and that of the FPC scores.…”

Section: Introductionmentioning

confidence: 99%

Classification via principal differential analysis

Jang

Lim

2021

CSAM

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We propose principal differential analysis based classification methods. Computations of squared multiple correlation function (RSQ) and principal differential analysis (PDA) scores are reviewed; in addition, we combine principal differential analysis results with the logistic regression for binary classification. In the numerical study, we compare the principal differential analysis based classification methods with functional principal component analysis based classification. Various scenarios are considered in a simulation study, and principal differential analysis based classification methods classify the functional data well. Gene expression data is considered for real data analysis. We observe that the PDA score based method also performs well.

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Section: Introductionmentioning

confidence: 99%