Functional Mixture Discriminant Analysis with hidden process regression for curve classification
We present a new mixture model-based discriminant analysis approach for functional data using a specific hidden process regression model. The approach allows for fitting flexible curve-models to each class of complex-shaped curves presenting regime changes. The model parameters are learned by maximizing the observed-data log-likelihood for each class by using a dedicated expectation-maximization (EM) algorithm. Comparisons on simulated data with alternative approaches show that the proposed approach provides better results.
Code (0)
등록된 구현이 없습니다.
Tasks
General ClassificationregressionSimilar Papers 제목 키워드 기반
Model-based functional mixture discriminant analysis with hidden process regression for curve classification
In this paper, we study the modeling and the classification of functional data presenting regime changes over time. We propose a new model-based functional mixture discriminant analysis approach based on a specific hidde…
General ClassificationregressionMixture model-based functional discriminant analysis for curve classification
Statistical approaches for Functional Data Analysis concern the paradigm for which the individuals are functions or curves rather than finite dimensional vectors. In this paper, we particularly focus on the modeling and …
ClassificationGeneral ClassificationregressionModel-Based Clustering and Classification of Functional Data
The problem of complex data analysis is a central topic of modern statistical science and learning systems and is becoming of broader interest with the increasing prevalence of high-dimensional data. The challenge is to …
ClassificationClusteringGeneral Classificationmodel+1A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis
This paper proposes a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the comp…
Dimensionality ReductionEEGElectroencephalogram (EEG)General Classification+2Bayesian Fisher's Discriminant for Functional Data
We propose a Bayesian framework of Gaussian process in order to extend Fisher's discriminant to classify functional data such as spectra and images. The probability structure for our extended Fisher's discriminant is exp…