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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Multiclass Sparse Discriminant Analysis Incorporating Graphical Structure among Predictors
预测变量 图形结构 多类稀疏 判别分析
2023/5/9
In the era of big data, many sparse linear discriminant analysis methods have been proposed for the classification and variable selection of the high-dimensional data. In order to solve the multiclass...
Comparison of partial least squares-discriminant analysis, support vector machines and deep neural networks for spectrometric classification of seed vigour in a broad range of tree species
least squares-discriminant analysis spectrometric classification seed tree species
2023/6/5
Seed vigour significantly influences the seed production and plant regeneration performance. The capability of NIR spectroscopy to identify seed vigour across multiple tree species rapidly and cost-ef...
Discriminant analysis of colour measurements reveals allele dosage effect of ASIP/MC1R in bay horses
horse coat colour ASIP MC1R CIE L*a*b
2018/11/23
Considering the variability of bay coat colour, we aimed to investigate the association of different shades of bay with ASIP and MC1R genotype combinations and we studied the discrimination between th...
A SATELLITE IMAGE CLASSIFICATION APPROACH BY USING ONE DIMENSIONAL DISCRIMINANT ANALYSIS
Satellite Image Image Classification Linear Discriminant Analysis Dimension Reduction
2018/4/18
The classification problem in the image processing field is an important challenge, so that in the process image pixels are separated into previously determined classes according to their features. Th...
A SATELLITE IMAGE CLASSIFICATION APPROACH BY USING ONE DIMENSIONAL DISCRIMINANT ANALYSIS
Satellite Image Image Classification Linear Discriminant Analysis Dimension Reduction
2018/5/8
The classification problem in the image processing field is an important challenge, so that in the process image pixels are separated into previously determined classes according to their features. Th...
A Novel Use of Kernel Discriminant Analysis as a Higher-Order Side-Channel Distinguisher
Kernel Discriminant Analysis Higher-order Side Channel Analysis Side Channel Distinguisher
2017/11/1
Distinguishers play an important role in Side Channel Analysis (SCA), where real world leakage information is compared against hypothetical predictions in order to guess at the underlying secret key. ...
UNSUPERVISED WISHART CLASSFICATION OF WETLANDS IN NEWFOUNDLAND,CANADA USING POLSAR DATA BASED ON FISHER LINEAR DISCRIMINANT ANALYSIS
Polarimetric Synthetic Aperture Radar (PolSAR) Unsupervised Wishart Classification Fisher Linear Discrimination Feature Weighting
2016/11/23
Polarimetric Synthetic Aperture Radar (PolSAR) imagery is a complex multi-dimensional dataset, which is an important source of information for various natural resources and environmental classificatio...
On BIC's Selection Consistency for Discriminant Analysis
BIC Discriminant Analysis Selection Consistency
2016/1/19
Linear and quadratic discriminant analysis are two very useful classification methods, for which the problem of variable selection is of fundamental impor-tance. To this end, a BIC-type selection crit...
HYPERSPECTRAL IMAGE FEATURE EXTRACTION BASED ON GENERALIZED DISCRIMINANT ANALYSIS
Hyperspectral Image Feature Extraction Generalized Discriminant Analysis Kernel Function
2015/12/30
The hyperspectral image enriches spectrum information, so compared with panchromatic image and multispectral image; it can classify the ground target better. The feature extraction of hyperspectral im...
Longitudinal Discriminant Analysis of Hemoglobin Level for Predicting Preeclampsia
Discriminant Analysis Preeclampsia Hemoglobin
2015/10/22
Background: Preeclampsia is one of the most serious complications during pregnancy with important effects on health of mother and fetus that causes maternal and fetal morbidity and mortality. This stu...
Functional Linear Discriminant Analysis for Irregularly Sampled Curves
Classification Filtering Functional data Linear discriminant analysis Low dimensional representation Reduced rank Regularized discriminant analysis Sparse curves
2015/8/21
We introduce a technique for extending the classical method of Linear Discriminant Analysis to data sets where the predictor variables are curves or functions. This procedure, which we call functional...
Feature Extraction for Nonparametric Discriminant Analysis
ClassiŽ cation Density estimation Dimension reduction LDA Projection pursuit Reduced-rankmodel SAVE
2015/8/21
In high-dimensional classification problems, one is often interested in ?? finding a few important discriminant directions in order to reduce the dimensionality.Fisher’s linear discriminant analysis(L...
Regularized linear discriminant analysis and its application in microarrays
Regularized linear discriminant analysis microarrays
2015/8/21
In this paper, we introduce a modified version of linear discriminant analysis, called the “shrunken centroids regularized discriminant analysis” (SCRDA). This method generalizes the idea of the “near...
We consider the problem of performing interpretable classification in the high-dimensional setting, in which the number of features is very large and the number of observations is limited. This settin...
Investigating of geometrical and asymptotical properties of hyperspectral data for discriminant analysis
Hyperspectral Feature extraction Discriminant analysis
2015/8/20
Hyperspectral images provide abundant information about objects. The high dimensionality of such images arise various problems
such as curse of dimensionality and large hypothesis space. There are tw...