This paper presents, for the first time, unsupervised discriminative training of probabilistic linear discriminant analysis (unsupervised DT-PLDA). While discriminative training avoids the problem of generative training based on probabilistic model assumptions that often do not agree with actual data, it has been difficult to apply it to unsupervised scenarios because it can fit data with almos...

We study discriminative joint density models, that is, generative models for the joint density p(c,x) learned by maximizing a discriminative cost function, the conditional likelihood. We use the framework to derive generative models for generalized linear models, including logistic regression, linear discriminant analysis, and discriminative mixture of unigrams. The benefits of deriving the dis...

classical lbp such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. in this paper, we introduce an improved lbp algorithm to solve these problems that utilizes fast pca algorithm for reduction of vector dimensions of extracted features. in other words, proffer method (fast pca+lbp) is an improved lbp algorithm that is extracted ...

Studies on the distribution of traffic demands have been proceeding by providing traffic information for reducing greenhouse gases and reinforcing the road's competitiveness in the transport section, however, since it is preferentially required the extensive studies on the driver's behavior changing routes and its influence factors, this study has been developed a discriminant model for changin...

A binary neural network classifier is evaluated against linear discriminant analysis within the framework of a statistical model for forecasting tropical cyclogenesis (TCG). A dataset consisting of potential developing cloud clusters which formed during the 1998-2001 Atlantic hurricane seasons is used in conjunction with eight large-scale predictors of TCG. Each predictor value is calculated at...

This work shows that 5 out of 6 acoustic parameters that correctly classify read and narrated speech in Brazilian Portuguese are temporal parameters. Several statistical models showed that significant differences between the styles are revealed by: speech rate, a measure of articulation rate, duration-related salience rate, mean and standard-deviation of degree of duration-related salience and ...

Recursive modeling is an attractive data-analytic tool for studying the relationship between a dependent variable and a collection of predictor variables. In this, it complements methods such as multiple regression, analysis of variance, neural nets, generalized additive models, discriminant analysis and log linear modeling. It is particularly helpful when simple models like regression do not w...

rapid exploratory field survey, to identify indigenous chicken ecotypes was conducted in north gondar zone of ethiopia. chicken ecotypes including necked neck, gasgie and gugut from quara, alefa and tache armacheho districts were identified, respectively. morphological variations among the three study populations and nine measurable traits were evaluated. general linear model, canonical discrim...

when the number of training samples is limited, feature reduction plays an important role in classification of hyperspectral images. in this paper, we propose a supervised feature extraction method based on discriminant analysis (da) which uses the first principal component (pc1) to weight the scatter matrices. the proposed method, called da-pc1, copes with the small sample size problem and has...

A mixed integer programming model is proposed for multiple-class discriminant and classification analysis. When multiple discriminant functions, one for each class, are constructed with the mixed integer programming model, the number of misclassified observations in the sample is minimized. Although having its own right, this model may be considered as a generalization of mixed integer programm...