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Classification croisée et modèles

Y. Bencheikh (2010)

RAIRO - Operations Research

The relations between automatic clustering methods and inferentiel statistical models have mostely been studied when the data involves only one set. We propose to study these relations in the case of data involving two sets. We shall look at cross clustering methods as suggested by Govaert [6]; we show that these methods, like the simple clustering methods, can be considered as a clustering approach of a mixture model. We introduce the notion of crossed mixture from a concret example and...

Classification in the Gabor time-frequency domain of non-stationary signals embedded in heavy noise with unknown statistical distribution

Ewa Świercz (2010)

International Journal of Applied Mathematics and Computer Science

A new supervised classification algorithm of a heavily distorted pattern (shape) obtained from noisy observations of nonstationary signals is proposed in the paper. Based on the Gabor transform of 1-D non-stationary signals, 2-D shapes of signals are formulated and the classification formula is developed using the pattern matching idea, which is the simplest case of a pattern recognition task. In the pattern matching problem, where a set of known patterns creates predefined classes, classification...

Classification into two von Mises distributions with unknown mean directions

Kryštof Eben (1983)

Aplikace matematiky

The paper deals with two Mises distributions on the circle with unknown mean directions and a common concentration parameter that is known. The likelihood rule and the plug-in rule are examined. For the statistic of the plug-in rule, the moment generating function is given and a method of obtaining the moments is proposed.

Classification of Images Background Subtraction in Image Segmentation

Francesco Mola, Jaromír Antoch, Luca Frigau, Claudio Conversano (2016)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

Many image segmentation algorithms have been proposed to partition an image into foreground regions of interest and background regions to be ignored. These algorithms use pixel intensities to partition the image, so it should be good practice to choose an appropriate background color as different as possible from the foreground one. In the case of a unique digitizing operation the user can make the choice of background color by himself in order to obtain a good result in the segmentation process,...

Classification of Smoking Cessation Status Using Various Data Mining Methods

Kartelj, Aleksandar (2010)

Mathematica Balkanica New Series

AMS Subj. Classification: 62P10, 62H30, 68T01This study examines different approaches of binary classification applied to the prob- lem of making distinction between former and current smokers. Prediction is based on data collected in national survey performed by the National center for health statistics of America in 2000. The process consists of two essential parts. The first one determines which attributes are relevant to smokers status, by using methods like basic genetic algorithm and different evaluation...

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