Xem 1-9 trên 9 kết quả Pca method
  • We introduce a new method for disambiguating word senses that exploits a nonlinear Kernel Principal Component Analysis (KPCA) technique to achieve accuracy superior to the best published individual models. We present empirical results demonstrating significantly better accuracy compared to the state-of-the-art achieved by either na¨ve Bayes ı or maximum entropy models, on Senseval-2 data. We also contrast against another type of kernel method, the support vector machine (SVM) model, and show that our KPCA-based model outperforms the SVM-based model. ...

    pdf8p bunbo_1 17-04-2013 16 1   Download

  • This is the first book in a three-volume series deploying MATLAB-based applications in almost every branch of science. This volume, presents interesting topics from different areas of engineering, signal and image processing based on the MATLAB environment. The book consists of 20 excellent, insightful articles and the readers will find the results very useful to their work. This collection of high quality articles, refers to a large range of professional fields and may be used for scientific, engineering and educational purposes....

    pdf0p cucdai_1 16-10-2012 72 28   Download

  • This chapter starts by reviewing some of the early research efforts in independent component analysis (ICA), especially the technique based on nonlinear decorrelation, that was successfully used by Jutten, H´ rault, and Ans to solve the first ICA problems. e Today, this work is mainly of historical interest, because there exist several more efficient algorithms for ICA. Nonlinear decorrelation can be seen as an extension of second-order methods such as whitening and principal component analysis (PCA)....

    pdf24p duongph05 09-06-2010 82 10   Download

  • Các thành phần chủ yếu, nhân tố, và phân tích cụm, và ứng dụng trong phân tích khu vực xã hội Chương này thảo luận về ba phương pháp phân tích đa biến quan trọng thống kê: thành phần chủ yếu phân tích (PCA), phân tích yếu tố (FA), và phân tích cluster (CA). PCA và FA thường được sử dụng với nhau để giảm dữ liệu bằng cách cơ cấu nhiều biến thành một số hạn chế của các thành phần (yếu tố).

    pdf21p hoakimthienduong 19-12-2011 36 10   Download

  • ICA by Nonlinear Decorrelation and Nonlinear PCA This chapter starts by reviewing some of the early research efforts in independent component analysis (ICA), especially the technique based on nonlinear decorrelation, that was successfully used by Jutten, H´ rault, and Ans to solve the first ICA problems. e Today, this work is mainly of historical interest, because there exist several more efficient algorithms for ICA. Nonlinear decorrelation can be seen as an extension of second-order methods such as whitening and principal component analysis (PCA).

    pdf24p khinhkha 29-07-2010 50 9   Download

  • Face recognition is still a vividly researched area in computer science. First attempts were made in early 1970-ies, but a real boom happened around 1988, parallel with a large increase in computational power. The first widely accepted algorithm of that time was the PCA or eigenfaces method, which even today is used not only as a benchmark method to compare new methods to, but as a base for many methods derived from the original idea.

    pdf246p bi_bi1 11-07-2012 33 6   Download

  • The paper presents and discusses the methodology used and the results obtained by the application of the Principal Component Analysis (PCA) on a set of socio-economical and land use data collected in the Duy Tien district (Ha Nam province), Vietnam. Objective of this study is to use PCA as a data reduction method to verify if a relation could be established between the quantities of waste generated in a region and its land use and socio-economical characteristics.

    pdf11p dem_thanh 22-12-2012 30 4   Download

  • Daruwalla et al. Journal of Orthopaedic Surgery and Research 2010, 5:21 http://www.josr-online.com/content/5/1/21 RESEARCH ARTICLE Open Access An application of principal component analysis to the clavicle and clavicle fixation devices Zubin J Daruwalla1*, Patrick Courtis2, Clare Fitzpatrick2, David Fitzpatrick2, Hannan Mullett1 Abstract Background: Principal component analysis (PCA) enables the building of statistical shape models of bones and joints. This has been used in conjunction with computer assisted surgery in the past. However, PCA of the clavicle has not been performed.

    pdf8p sting01 15-01-2012 24 3   Download

  • We initiate a study comparing effectiveness of the transformed spaces learned by recently proposed supervised, and semisupervised metric learning algorithms to those generated by previously proposed unsupervised dimensionality reduction methods (e.g., PCA). Through a variety of experiments on different realworld datasets, we find IDML-IT, a semisupervised metric learning algorithm to be the most effective.

    pdf5p hongdo_1 12-04-2013 17 2   Download

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