Classification results based on the discriminant analysis
Object Classification with Classical Linear Discriminant Analysis and Robust Linear Discriminant Analysis
... Abstract: Discriminant analysis is one of multivariate analysis with dependency ...method. Discriminant analysis is a multivariate analysis that aims to classify observations ...
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Classification efficiencies for robust linear discriminant analysis.
... phrases: Classification efficiency, Discriminant analysis, Error rate, Fisher rule, Influence function, ...In discriminant analysis one observes several groups of multivariate observa- ...
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Dynamic probabilistic linear discriminant analysis for video classification
... For LDA, we computed the distance between all the frames of the first video in a pair from all the frames in the second video of the same pair. Their average is regarded as a video-to-video distance. When considering a ...
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Comparison of linear discriminant analysis methods for the classification of cancer based on gene expression data
... cancer based on gene expression data have been reported in great detail, however, one major challenge for the methodologists is the choice of classification ...linear discriminant analysis ...
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Relevance Vector Machine Classification of Hyperspectral Data Based on Principal Component Analysis and Linear Discriminant Analysis
... Results and Discussion A sample hyperspectral image which is taken over northwest Indiana's Indian Pine test site in June 1992 is used to test the proposed algorithm. The Indian Pine data consists of 145×145 ...
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Correlation-based linear discriminant classification for gene expression data.
... DOI http://dx.doi.org/10.4238/gmr16019357 Copyright © 2017 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution ShareAlike (CC BY-SA) 4.0 License. ABSTRACT. ...
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Imprecise Gaussian Discriminant Classification
... Gaussian discriminant analysis is a popular classifica- tion model, that in the precise case can produce unre- liable predictions in case of high ...nant analysis based on robust Bayesian ...
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Generalized Sparse Discriminant Analysis for Event-Related Potential Classification
... An analysis of the J-divergence as a function of channel and time allowed us to detect the most discriminative ...KLD discriminant infor- mation was introduced into the GSDA formulation through the ...
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Dropout Classification through Discriminant Function Analysis: A Statistical Approach
... this, classification models can be designed that can predict whether the student is thinking about the dropout from the ...a classification model for the dropout using a statistical technique called ...
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Discriminant Analysis with Spatial Weights for Urban Land Cover Classification
... vegetation also became irregular as well. This is because the DASW algorithm is based on an n by n window, equally spaced from a central pixel. The calculation of geographical weight is derived from the inversed ...
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Variable selection in model-based discriminant analysis
... la classification supervis´ ee, soit des variables redondantes, li´ es aux pr´ edicteurs par une r´ egression lin´ eaire, soit des variables ind´ ...en classification non supervis´ ee par des mod` eles de ...
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Genotype imputation based on discriminant and cluster analysis
... The recent development of high-throughput systems for genotyping SNP in Eukaryote has led to an extraordinary amount of research activity, particularly in areas such as whole- genome selection of livestock and ...
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Support Vector Machine based Classification into Groups using Discriminant Function
... for classification and regression ...a classification tasks by constructing an optimal separating hyper plane that maximizes the margin between the two nearest data points belonging to two separate ...is ...
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Discriminant Analysis
... L(1, 2) · (the probability for misclassification if π 1 is true) = L(2, 1) · (the probability for misclassification if π 2 is true) Since one is an increasing and the other a decreasing function of c it is obvious that ...
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Linear Discriminant Analysis for Two Classes via Removal of Classification Structure
... (3) REM can be applied to any discriminant criterion which determines a single linear one- dimensional subspace of the sample space. Acknowledgments The author wishes to thank associate editor Prof. ...
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Image Processing System for Air Classification Using Linear Discriminant Analysis
... An image’s regions of interest are objects (Cu particles) in its foreground. However, the particles having a color similar to the background color are bu- ried in the background. Using the difference of two color ...
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Robust linear discriminant analysis for multiple groups: influence and classification efficiencies.
... “consistent”, in the sense of not being asymptotically optimal, and one cannot compute asymptotic relative efficiencies. This is comparable to the asymptotic efficiency of an estimator, which can only be compared among ...
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Application of linear discriminant analysis in dimensionality reduction for hand motion classification
... RESEARCH Based on the classification results with a linear discriminant classifier, and a 4-channel, 8-movement EMG system, ULDA, OLDA and OFNDA are suitable for use as dimensionality ...
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Classification of root canal microorganisms using electronic-nose and discriminant analysis
... trained based on the rest of the samples and the resultant test error rates are averaged to obtain the 5-fold CV error ...CV classification error is more costly ...CV classification error estimation ...
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Classification and Identification of IDP Camps After Mosul Events Based on Epidemics and Other Factors Using Cluster Analysis and Discriminant Analysis
... statistical analysis methods were applied. The Cluster Analysis method was used to identify the disparities in the distribution of IDP camps among the Iraqi governorates after Mosul events in terms of the ...
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