Free Download Analysis of Multivariate and High-Dimensional Data (Cambridge Series in Statistical and Probabilistic Mathematics)
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Book Details :
Published on: 2013-12-02
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Original language: English
"Big data" poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed "safe operating zone" for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/ graduate students in statistics and researchers in data-rich disciplines. �� Members of the Statistical Laboratory Members of the Statistical Laboratory . Director ; Academic Staff ; Affiliated Lecturers ; Emeritus Academic Staff; Research Staff ; Visiting Fellows ; Research Students Analysis of variance - Wikipedia As exploratory data analysis an ANOVA is an organization of an additive data decomposition and its sums of squares indicate the variance of each component of the ... Research Fellows - The Alan Turing Institute BIO. Joshua Loftus is a statistician and data scientist with research interests in high-dimensional statistics and post-selection inference and more broadly in ... The Gaussian Processes Web Site The Gaussian Processes Web Site. This web site aims to provide an overview of resources concerned with probabilistic modeling inference and learning based on ... Events - The Alan Turing Institute Category Title Date Location Additional info date-order; Other Machine Learning Theory Part 1: TBC The Alan Turing Institute Speaker 1: Varun Kanade . 13 ... Machine Learning Group Publications - University of Cambridge Tomoharu Iwata James Robert Lloyd and Zoubin Ghahramani. Unsupervised many-to-many object matching for relational data. IEEE Transactions on Pattern Analysis and ... Accepted Papers ICML New York City Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues Nihar Shah UC Berkeley Sivaraman Balakrishnan CMU Aditya Guntuboyina ... Topics in Statistical Data Analysis: Revealing Facts from Data Revealing Facts From Data. USA Site. This site offers information on statistical data analysis. It describes time series analysis popular distributions and other ... Publications Page - Cambridge Machine Learning Group [ full BibTeX file] 2017 2016. Matej Balog Alexander L. Gaunt Marc Brockschmidt Sebastian Nowozin and Daniel Tarlow. DeepCoder: Learning to write programs. Least squares - Wikipedia The method of least squares is a standard approach in regression analysis to the approximate solution of overdetermined systems i.e. sets of equations in which ...
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