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Correct Classification Rates in Multi-Category Discriminant Analysis of Spatial Gaussian Data

by Lina Dreižienė, Kęstutis Dučinskas, Laura Paulionienė
"... This paper discusses the problem of classifying a multivariate Gaussian random field observation into one of the several categories specified by different parametric mean models. Investigation is conducted on the classifier based on plug-in Bayes classification rule (PBCR) formed by replacing unknow ..."
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unknown parameters in Bayes classification rule (BCR) with category parameters estimators. This is the extension of the previous one from the two category cases to the multi-category case. The novel closed-form expressions for the Bayes classification probability and actual correct classifi-cation rate

N-grambased text categorization

by William B. Cavnar, John M. Trenkle - In Proc. of SDAIR-94, 3rd Annual Symposium on Document Analysis and Information Retrieval , 1994
"... Text categorization is a fundamental task in document processing, allowing the automated handling of enormous streams of documents in electronic form. One difficulty in handling some classes of documents is the presence of different kinds of textual errors, such as spelling and grammatical errors in ..."
Abstract - Cited by 445 (0 self) - Add to MetaCart
is small, fast and robust. This system worked very well for language classification, achieving in one test a 99.8 % correct classification rate on Usenet newsgroup articles written in different languages. The system also worked reasonably well for classifying articles from a number of different computer

Shape matching and object recognition using low distortion correspondence

by Alexander C. Berg, Tamara L. Berg, Jitendra Malik - In CVPR , 2005
"... We approach recognition in the framework of deformable shape matching, relying on a new algorithm for finding correspondences between feature points. This algorithm sets up correspondence as an integer quadratic programming problem, where the cost function has terms based on similarity of correspond ..."
Abstract - Cited by 419 (15 self) - Add to MetaCart
datasets. One is the Caltech 101 dataset (Fei-Fei, Fergus and Perona), an extremely challenging dataset with large intraclass variation. Our approach yields a 48 % correct classification rate, compared to Fei-Fei et al’s 16%. We also show results for localizing frontal and profile faces that are comparable

Svm-knn: Discriminative nearest neighbor classification for visual category recognition

by Hao Zhang, Alexander C. Berg, Michael Maire, Jitendra Malik - in CVPR , 2006
"... We consider visual category recognition in the framework of measuring similarities, or equivalently perceptual distances, to prototype examples of categories. This approach is quite flexible, and permits recognition based on color, texture, and particularly shape, in a homogeneous framework. While n ..."
Abstract - Cited by 342 (10 self) - Add to MetaCart
variety of distance functions can be used and our experiments show state-of-the-art performance on a number of benchmark data sets for shape and texture classification (MNIST, USPS, CUReT) and object recognition (Caltech-101). On Caltech-101 we achieved a correct classification rate of 59

© Science and Education Publishing DOI:10.12691/ajams-3-4-3 Of Students Academic Performance Rates Using Artificial Neural Networks (ANNs)

by O. C. Asogwa, A. V. Oladugba , 2015
"... Abstract A model based on the multilayer perception algorithm was programmed. The result from the test data evaluation showed that the programmed Artificial Neural Network model was able to correctly predict and classify the performance of students with Mean Correct Classification Rate CCR of 97.07% ..."
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Abstract A model based on the multilayer perception algorithm was programmed. The result from the test data evaluation showed that the programmed Artificial Neural Network model was able to correctly predict and classify the performance of students with Mean Correct Classification Rate CCR of 97.07%.

A Comparison of Classification Methods for Forest Cover Type

by Alvin Au , Jared Eccles , André Haynes , Timothy Thatcher , Yicheng Zhang
"... Abstract This study evaluates the performance of seven classification techniques on the problem of predicting forest cover type from cartographic data. The data was obtained from the UCI Machine Learning Repository. Techniques are evaluated based on the metric of correct classification rate for eac ..."
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Abstract This study evaluates the performance of seven classification techniques on the problem of predicting forest cover type from cartographic data. The data was obtained from the UCI Machine Learning Repository. Techniques are evaluated based on the metric of correct classification rate

Wilkinson JM. 2013 Use of kernel-based

by Kadirkamanathan V , 2013
"... kernel density estimation, Bayes theorem, Author for correspondence: Use of kernel-based Bayesian models to predict late osteolysis dence of osteolysis. The correct classification rate using age and wear rate inElectronic supplementary material is available ..."
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kernel density estimation, Bayes theorem, Author for correspondence: Use of kernel-based Bayesian models to predict late osteolysis dence of osteolysis. The correct classification rate using age and wear rate inElectronic supplementary material is available

breast cancer data

by R. Jain, A. Abraham
"... In this paper, we examine the performance of four fuzzy rule generation methods on Wisconsin breast cancer data. The first method generates fuzzy if-then rules using the mean and the standard deviation of attribute values with 92.2% correct classification rate. The second approach generates fuzzy if ..."
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In this paper, we examine the performance of four fuzzy rule generation methods on Wisconsin breast cancer data. The first method generates fuzzy if-then rules using the mean and the standard deviation of attribute values with 92.2% correct classification rate. The second approach generates fuzzy

Automatic speech classification to five emotional states based on gender information

by Dimitrios Ververidis, Constantine Kotropoulos - in Proc. 2004 European Signal Processing Conf , 2004
"... Emotional speech recognition aims to automatically classify speech units (e.g., utterances) into emotional states, such as anger, happiness, neutral, sadness and surprise. The major contribution of this paper is to rate the discriminating capability of a set of features for emotional speech recognit ..."
Abstract - Cited by 27 (6 self) - Add to MetaCart
in the best way for each gender. The criterion used in SFS is the crossvalidated correct classification rate of a Bayes classifier where the class probability distribution functions (pdfs) are approximated via Parzen windows or modeled as Gaussians. When a Bayes classifier with Gaussian pdfs is employed, a

Printed in Great Britain Asymptotic expansions for the means and variances of error rates

by J. Schervish
"... The problem of classifying an observation X into one of k multivariate normal distributions is considered. When samples are used to estimate the population parameters, the probabilities of correct classification, and the associated error rates, are random variables. Asymptotic expansions for the exp ..."
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The problem of classifying an observation X into one of k multivariate normal distributions is considered. When samples are used to estimate the population parameters, the probabilities of correct classification, and the associated error rates, are random variables. Asymptotic expansions
Results 1 - 10 of 1,150