Distance-based directional depth classifiers: a robustness study
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Publication:6141745
DOI10.1080/03610918.2021.1996603OpenAlexW3216125264MaRDI QIDQ6141745
Houyem Demni, Amor Messaoud, Giovanni C. Porzio
Publication date: 23 January 2024
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2021.1996603
Cites Work
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- Robust estimation of location and concentration parameters for the von Mises-Fisher distribution
- On robust classification using projection depth
- On the optimality of the max-depth and max-rank classifiers for spherical data.
- Fast and robust discriminant analysis
- An outlier map for support vector machine classification
- Robustness of estimators for directional data
- Multivariate analysis by data depth: Descriptive statistics, graphics and inference. (With discussions and rejoinder)
- Depth-weighted Bayes classification
- On finite-sample robustness of directional location estimators
- Class noise vs. attribute noise: A quantitative study of their impacts
- General notions of statistical depth function.
- A new concept of quantiles for directional data and the angular Mahalanobis depth
- A robust approach to model-based classification based on trimming and constraints. Semi-supervised learning in presence of outliers and label noise
- Directional naive Bayes classifiers
- A survey of outlier detection methodologies
- Multivariate and functional classification using depth and distance
- Robust classification for skewed data
- Recent advances in directional statistics
- Rank-Based Classification Using Robust Discriminant Functions
- Discriminant Analysis for the von Mises-Fisher Distribution
- Measures of centrality for multivariate and directional distributions
- High-Breakdown Linear Discriminant Analysis
- Robust linear discriminant analysis using S-estimators
- DD-Classifier: Nonparametric Classification Procedure Based onDD-Plot
- Distance‐based depths for directional data
- Robust support vector machine for high-dimensional imbalanced data
- Robust Statistics