Principal Components Analysis
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Principal Component Analysis
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Author : I.T. Jolliffe
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Principal Component Analysis written by I.T. Jolliffe and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and developed independently by Hotelling (1933). Like many multivariate methods, it was not widely used until the advent of electronic computers, but it is now weIl entrenched in virtually every statistical computer package. The central idea of principal component analysis is to reduce the dimen sionality of a data set in which there are a large number of interrelated variables, while retaining as much as possible of the variation present in the data set. This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an eigenvalue-eigenvector problem for a positive-semidefinite symmetrie matrix. Thus, the definition and computation of principal components are straightforward but, as will be seen, this apparently simple technique has a wide variety of different applications, as weIl as a number of different deri vations. Any feelings that principal component analysis is a narrow subject should soon be dispelled by the present book; indeed some quite broad topics which are related to principal component analysis receive no more than a brief mention in the final two chapters.
Principal Components Analysis
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Author : George H. Dunteman
language : en
Publisher: SAGE
Release Date : 1989-05
Principal Components Analysis written by George H. Dunteman and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989-05 with Mathematics categories.
For anyone in need of a concise, introductory guide to principal components analysis, this book is a must. Through an effective use of simple mathematical-geometrical and multiple real-life examples (such as crime statistics, indicators of drug abuse, and educational expenditures) -- and by minimizing the use of matrix algebra -- the reader can quickly master and put this technique to immediate use.
Principal Components Analysis
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Author : George Henry Dunteman
language : en
Publisher:
Release Date : 1989
Principal Components Analysis written by George Henry Dunteman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Principal components analysis categories.
A User S Guide To Principal Components
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Author :
language : en
Publisher:
Release Date : 2005
A User S Guide To Principal Components written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Don't get bogged down in theoretical matters and computational techniques. Focus instead on practical aspects of data reduction and interpretation. Dealing with the "how-to-do-it" as well as the '"why-it-works," this paperback edition of a Wiley bestseller is designed for practitioners of principal component analysis. Among the topics explored are extension to p variables, scaling input data, inferential procedures, operations with group data, and vector interpretation.
A User S Guide To Principal Components
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Author : J. Edward Jackson
language : en
Publisher: John Wiley & Sons
Release Date : 2005-01-21
A User S Guide To Principal Components written by J. Edward Jackson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-21 with Mathematics categories.
WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selectedbooks that have been made more accessible to consumers in an effortto increase global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. From the Reviews of A User’s Guide to PrincipalComponents "The book is aptly and correctly named–A User’sGuide. It is the kind of book that a user at any level, novice orskilled practitioner, would want to have at hand for autotutorial,for refresher, or as a general-purpose guide through the maze ofmodern PCA." –Technometrics "I recommend A User’s Guide to Principal Components toanyone who is running multivariate analyses, or who contemplatesperforming such analyses. Those who write their own software willfind the book helpful in designing better programs. Those who useoff-the-shelf software will find it invaluable in interpreting theresults." –Mathematical Geology
Principal Component Analysis Handbook
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Author : Rebecca Cross
language : en
Publisher:
Release Date : 2015-02-19
Principal Component Analysis Handbook written by Rebecca Cross and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-19 with Principal components analysis categories.
This book on Principal component analysis (PCA) is a significant contribution to the field of data analysis. PCA involves a statistical procedure which orthogonally transforms a set of possibly correlated observations into set of values of linearly uncorrelated variables called principal components. The aim of this book is to enhance knowledge of scientists, engineers and researchers regarding the advantages of this technique in data analysis and includes information on the uses of PCA in distinct fields like multi-sensor data fusion, ecology, energy, agriculture, climate, image and video processing, gas chromatographic examination, color coating, materials science and automatic target identification.
Python Data Science Handbook
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Author : Jake VanderPlas
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-11-21
Python Data Science Handbook written by Jake VanderPlas and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Computers categories.
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Principal Components Analysis
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Author : Graeme D. Hutcheson
language : en
Publisher:
Release Date : 2020
Principal Components Analysis written by Graeme D. Hutcheson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Anthropology categories.
Principal component analysis (PCA) is a technique that essentially converts observed correlated variables into unobserved uncorrelated components. This enables a data set containing many individual variables to be described using a small number of components that capture much of the variation in the data set. PCA has a long history in statistics and has been applied in many disciplines including biology, astronomy, geography, social sciences, meteorology and management. In addition to reducing the number of variables required to describe a data set, PCA can also identify underlying mechanisms that may have played a role in determining the structure in the data (i.e., the underlying "Bcauses"). The reduction of a large number of variables to a relatively small number of components also enables a data set to be more easily analysed and described using other techniques. In particular, as the components identified by PCA are uncorrelated, many of the problems associated with multicollinearity are alleviated, enabling regression models to be more easily interpreted. This entry provides a relatively nontechnical and practical introduction to the application of PCA using a readily available data set and open-source software.
Topics In Cryptology Ct Rsa 2012
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Author : Orr Dunkelman
language : en
Publisher: Springer
Release Date : 2012-02-23
Topics In Cryptology Ct Rsa 2012 written by Orr Dunkelman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-23 with Computers categories.
This book constitutes the refereed proceedings of the Cryptographers' Track at the RSA Conference 2012, CT-RSA 2012, held in San Francisco, CA, USA, in February/March 2012. The 26 revised full papers presented were carefully reviewed and selected from 113 submissions. The papers are organized in topical sections on side channel attacks, digital signatures, public-key encryption, cryptographic protocols, secure implementation methods, symmetric key primitives, and secure multiparty computation.
Principal Component Analysis
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Author : Parinya Sanguansat
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-03-07
Principal Component Analysis written by Parinya Sanguansat and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-07 with Computers categories.
This book is aimed at raising awareness of researchers, scientists and engineers on the benefits of Principal Component Analysis (PCA) in data analysis. In this book, the reader will find the applications of PCA in fields such as energy, multi-sensor data fusion, materials science, gas chromatographic analysis, ecology, video and image processing, agriculture, color coating, climate and automatic target recognition.