دورية أكاديمية

New Routes from Minimal Approximation Error to Principal Components

التفاصيل البيبلوغرافية
العنوان: New Routes from Minimal Approximation Error to Principal Components
المؤلفون: Abhilash Alex, Er Mir, Yann-aël Le Borgne
المساهمون: The Pennsylvania State University CiteSeerX Archives
المصدر: http://www.ulb.ac.be/di/map/yleborgn/pub/NPL_PCA_07.pdfTest.
سنة النشر: 2007
المجموعة: CiteSeerX
مصطلحات موضوعية: principal components analysis, eigenvalue, matrix trace
الوصف: We introduce two new methods of deriving the classical PCA in the framework of minimizing the mean square error upon performing a lower-dimensional approximation of the data. These methods are based on two forms of the mean square error function. One of the novelties of the presented methods is that the commonly employed process of subtraction of the mean of the data becomes part of the solution of the optimization problem and not a pre-analysis heuristic. We also derive the optimal basis and the minimum error of approximation in this framework and demonstrate the elegance of our solution in comparison with an existing solution in the framework.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
العلاقة: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.9239Test; http://www.ulb.ac.be/di/map/yleborgn/pub/NPL_PCA_07.pdfTest
الإتاحة: http://www.ulb.ac.be/di/map/yleborgn/pub/NPL_PCA_07.pdfTest
حقوق: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
رقم الانضمام: edsbas.71962410
قاعدة البيانات: BASE