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搜索结果: 1-15 共查到Discriminant Analysis相关记录55条 . 查询时间(0.078 秒)
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...
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...
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...
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...
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...
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. ...
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...
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...
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...
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...
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...
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...
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...
Sparse Discriminant Analysis     Sparse  Discriminant Analysis       2015/8/21
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...
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...

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