Nonparametric plug-in classifier for multiclass classification of S.D.E. paths

2022-12-20 · Christophe Denis, Charlotte Dion-Blanc, Eddy Ella Mintsa, Viet-Chi Tran

We study the multiclass classification problem where the features come from the mixture of time-homogeneous diffusions. Specifically, the classes are discriminated by their drift functions while the diffusion coefficient is common to all classes and unknown. In this framework, we build a plug-in classifier which relies on nonparametric estimators of the drift and diffusion functions. We first establish the consistency of our classification procedure under mild assumptions and then provide rates of cnvergence under different set of assumptions. Finally, a numerical study supports our theoretical findings.

📄 PDF Abstract BibTeX arXiv:2212.10259

Code (1)

eddymichelella/sdeclassif 공식 구현

Tasks

Classification

Methods 이 논문이 사용한 방법론

Diffusion Diffusion models generate samples by gradually removing noise from a signal, and their training objective can be expressed as a reweighted variational lower-bound…

On a Theory of Nonparametric Pairwise Similarity for Clustering: Connecting Clustering to Classification

2014-12-01 · NeurIPS 2014 12 · Yingzhen Yang, Feng Liang, Shuicheng Yan, Zhangyang Wang 외

Pairwise clustering methods partition the data space into clusters by the pairwise similarity between data points. The success of pairwise clustering largely depends on the pairwise similarity function defined over the d…

Clustering Density Estimation General Classification Multi-class Classification

Generalization Error Bounds for Multiclass Sparse Linear Classifiers

2022-04-13 · Tomer Levy, Felix Abramovich

We consider high-dimensional multiclass classification by sparse multinomial logistic regression. Unlike binary classification, in the multiclass setup one can think about an entire spectrum of possible notions of sparsi…

Binary Classification feature selection regression

Learning From Non-iid Data: Fast Rates for the One-vs-All Multiclass Plug-in Classifiers

2014-08-12 · Vu Dinh, Lam Si Tung Ho, Nguyen Viet Cuong, Duy Nguyen 외

We prove new fast learning rates for the one-vs-all multiclass plug-in classifiers trained either from exponentially strongly mixing data or from data generated by a converging drifting distribution. These are two typica…

All

Consistent Classification with Generalized Metrics

2019-08-24 · Xiaoyan Wang, Ran Li, Bowei Yan, Oluwasanmi Koyejo

We propose a framework for constructing and analyzing multiclass and multioutput classification metrics, i.e., involving multiple, possibly correlated multiclass labels. Our analysis reveals novel insights on the geometr…

Classification General Classification

Nonparametric Unsupervised Classification

2012-10-02 · Yingzhen Yang, Thomas S. Huang

Unsupervised classification methods learn a discriminative classifier from unlabeled data, which has been proven to be an effective way of simultaneously clustering the data and training a classifier from the data. Vario…

Classification Clustering General Classification