Robust probabilistic classification applicable to irregularly sampled functional data

Yeonjoo Park, Douglas G Simpson

Research output: Contribution to journalArticle

Abstract

A robust probabilistic classifier for functional data is developed to predict class membership based on functional input measurements and to provide a reliable probability estimate for class membership. The method combines a Bayes classifier and semi-parametric mixed effects model with robust tuning parameter to make the method robust to outlying curves, and to improve the accuracy of the risk or uncertainty estimates, which is crucial in medical diagnostic applications. The approach applies to functional data with varying ranges and irregular sampling without making parametric assumptions on the within-curve covariance. Simulation studies evaluate the proposed method and competitors in terms of sensitivity to heavy tailed functional distributions and outlying curves. Classification performance is evaluated by both error rate and logloss, the latter of which imposes heavier penalties on highly confident errors than on less confident errors. Run-time experiments on the R implementation indicate that the proposed method scales well computationally. Illustrative applications include data from quantitative ultrasound analysis and phoneme recognition.

Original languageEnglish (US)
Pages (from-to)37-49
Number of pages13
JournalComputational Statistics and Data Analysis
Volume131
DOIs
StatePublished - Mar 2019

Fingerprint

Functional Data
Curve
Classifiers
Irregular Sampling
Bayes Classifier
Mixed Effects Model
Parameter Tuning
Robust Methods
Ultrasound
Estimate
Error Rate
Penalty
Diagnostics
Tuning
Ultrasonics
Classifier
Simulation Study
Sampling
Uncertainty
Predict

Keywords

  • Bayes classifier
  • Mixed effects model
  • Probabilistic classification
  • Robustness
  • t-model

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

Cite this

Robust probabilistic classification applicable to irregularly sampled functional data. / Park, Yeonjoo; Simpson, Douglas G.

In: Computational Statistics and Data Analysis, Vol. 131, 03.2019, p. 37-49.

Research output: Contribution to journalArticle

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