Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Powiadomienia systemowe

Sesja wygasła!
Sesja wygasła!
Sesja wygasła!

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: contingency tables

Sortuj według:

Ogranicz wyniki do:

Nonparametric Versus Parametric Reasoning Based on 22 Contingency Tables

Sulewski P.

Computational Methods in Science and Technology

2018

Vol. 24, No. 2

143--153

This paper proposes scenarios of generating contingency tables (CTs) with the probability flow parameter (PFP). It also defines measures of untruthfulness of H0 that involve PFP for all proposed scenarios. This paper is an attempt to replace a nonparametric statistical inference method by the parametric one. The paper applies the maximum likelihood method to estimate PFP and presents instructions to generate CTs by means of the bar method. The Monte Carlo method is used to carry out computer simulations.

Membership function - ARTMAP neural networks

Sinčák P., Hric M., Vaščák J.

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

2003

Vol. 7, No 1

43-52

The project deals with the application of computational intelligence (CI) tools for multispectral image classification. Pattern Recognition scheme is a global approach where the classification part is playing an important role to achieve the highest classification accuracy. Multispectral images are data mainly used in remote sensing and this kind of classification is very difficult to assess the accuracy of classification results. There is a feedback problem in adjusting the parts of pattern recognition scheme. Precise classification accuracy assessment is almost impossible to obtain, being an extremely laborious procedure. The paper presents simple neural networks for multispectral image classification, ARTMAP-like neural networks as more sophisticated tools for classification, and a modular approach to achieve the highest classification accuracy of multispectral images. There is a strong link to advances in computer technology, which gives much better conditions for modelling more sophisticated classifiers for multispectral images.