Principal component discriminant analysis

被引：0

作者：

Fearn, Tom ^{[1
]}

机构：

[1] UCL, London WC1E 6BT, England

来源：

STATISTICAL APPLICATIONS IN GENETICS AND MOLECULAR BIOLOGY | 2008年 / 7卷 / 02期

关键词：

D O I：

暂无

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

The approach adopted involved two-stages. First the 11205 measurements in the mass spectrometry data were reduced to 14 scores by a principal component analysis of the centered but otherwise untreated and unscaled data matrix. Then a linear classifier was derived by linear discriminant analysis using these 14 scores as inputs. This number of scores was chosen by leave-one-out cross-validation on the training set, where it gave an overall error rate of 14%. Some indication of the information used in the classification may be obtained from an inspection of the coefficients of the linear classifier.

引用

页数：6

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