linear discriminant analysis中文是什么意思

發(fā)音:

中文翻譯
造句

線性判別分析

linear adj. 1.線的，直線的。 2.長(zhǎng)度的。 3.【數(shù)學(xué)】 ...
discriminant n. 【數(shù)學(xué)】判別式。
analysis n. (pl. -ses ) 1.分解，分析；【數(shù)學(xué)】解 ...
discriminant analysis 辨別分析; 差別分析; 差異分析法; 判別分析
linear discriminant function 線性判別函數(shù)
cluster and discriminant analysis 聚類判別分析
factorial discriminant analysis 多因辨別分析; 因子判別式分析
generalized discriminant analysis 廣義判別分析
gradual-discriminant analysis 逐步判別分析法
landsat discriminant analysis image 陸地衛(wèi)星判別分析圖象
multiple discriminant analysis 多變量判別分析法; 多重判別分析; 復(fù)判別分析; 復(fù)識(shí)別分析
standard nonlinear discriminant analysis 標(biāo)準(zhǔn)非線性判別分析
stepwise discriminant analysis 逐步判別分析
techniques of discriminant analysis 判別分析法
linear analysis 圖線分析; 線性分析
linear buckling analysis 線性彎曲分析
linear displacement analysis 線性位移分析
linear elastic analysis 線彈性分析
linear factor analysis 非線性因素分析
linear perturbation analysis 線性微擾分析
linear prediction analysis 線性預(yù)測(cè)分析
linear prediction analysis synthesis 線性預(yù)測(cè)分析合成法
linear programming analysis 線形規(guī)劃分析
linear regression analysis 線性回歸分析; 直線回歸分析
linear system analysis 線性系統(tǒng)分析

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例句與用法

Theory of fisher linear discriminant analysis and its application
線性鑒別分析的理論研究及其應(yīng)用
A study on personal credit scoring using linear discriminant analysis
線性判別式分析在個(gè)人信用評(píng)估中的應(yīng)用
A new two - dimensional linear discriminant analysis algorithm based on fuzzy set theory
基于模糊集理論的二維線性鑒別分析新方法
In this paper , we focus on two - class discriminating problem and chiefly study two types of linear discriminant analysis : principal component classifier ( pcc ) and fisher linear discriminant analysis ( flda )
本文就兩分類問題，研究了兩種線性判別：主分量分類器和fisher判別分析。
Linear projection analysis , including principal component analysis ( or k - l transform ) and fisher linear discriminant analysis , is the classical and popular technique for feature extraction
線性投影分析，包括主分量分析(或稱k - l變換)和fisher線性鑒別分析，是特征抽取中最為經(jīng)典和廣泛使用的辦法。
A face - recognition algorithm based on fisher linear discriminant analysis is studied in detail which combines principal component analysis ( pca ) based eigenface method and linear discriminant analysis ( lda ) method
該方法將基于主成分分析( pca )的特征臉方法和基于線性判別分析( lda )的分類方法有機(jī)的結(jié)合起來。
The inherent relationship between fisher linear discriminant analysis and karhunen - loeve expansion is revealed , i . e . , ulda is essentially equivalent to one classical k - l expansion method . moreover , we enhance ulda using the idea of another k - l expansion method , and finally an optimal k - l expansion method is developed
揭示了具有統(tǒng)計(jì)不相關(guān)性的線性鑒別分析與經(jīng)典的k - l展開方法的內(nèi)在關(guān)系，即不相關(guān)的線性鑒別分析方法與包含在類均值向量中判別信息的最優(yōu)壓縮方法是等價(jià)的，并在此基礎(chǔ)上導(dǎo)出了一種最優(yōu)k - l展開方法。
Feature extraction through 2 - order polynomial fit of the descending part of the response curve made possible a timesaving measurement process . the performances of two pattern recognition algorithms , namely principal component analysis ( pca ) and linear discriminant analysis ( lda ) in practical problems were discussed . artificial neural network ( ann ) was utilized with back - propagation algorithm ( bpa ) , and the combination of pca / lda with ann improved the identification performance of the system
基于對(duì)模式識(shí)別系統(tǒng)的深入研究，提出了從響應(yīng)階段數(shù)據(jù)提取特征的方法，節(jié)省了測(cè)試所需時(shí)間；比較了主成分分析法( principalcomponentanalysis , pca )與線性判別式法( lineardiscriminantanalysis , lda )兩種模式識(shí)別方法在實(shí)際應(yīng)用中的不同結(jié)果，分析了原因；設(shè)計(jì)了采用誤差反傳算法back - propagationalgorithm , bpa )的前向人工神經(jīng)網(wǎng)絡(luò)( artificialneuralnetwork , ann ) ，并指出其應(yīng)用中存在的問題，提出了改進(jìn)建議；利用pca lda與ann相結(jié)合的方法改善了系統(tǒng)的識(shí)別性能。
The conventional principal component analysis ( pca ) and fisher linear discriminant analysis ( lda ) are based on vectors . that is to say , if we use them to deal with the image recognition problem , the first step is to transform original image matrices into same dimensional vectors , and then rely on these vectors to evaluate the covariance matrix and to determine the projector
所提出的這兩種方法的共同特點(diǎn)是，在進(jìn)行圖像特征抽取時(shí)，不需要事先將圖像矩陣轉(zhuǎn)化為高維的圖像向量，而是直接利用圖像矩陣本身構(gòu)造圖像散布矩陣，然后基于這些散布矩陣進(jìn)行主分量分析與線性鑒別分析。

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百科解釋

Linear discriminant analysis (LDA) and the related Fisher's linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.

詳細(xì)百科解釋

其他語種釋義

linear discriminant analysisとは意味：線形判別分析｛せんけいはんべつぶんせき｝

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