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Advanced Methods Of Data Exploration And Modelling
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Book Synopsis Discrete Data Analysis with R by : Michael Friendly
Download or read book Discrete Data Analysis with R written by Michael Friendly and published by CRC Press. This book was released on 2015-12-16 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical meth
Book Synopsis Explanatory Model Analysis by : Przemyslaw Biecek
Download or read book Explanatory Model Analysis written by Przemyslaw Biecek and published by CRC Press. This book was released on 2021-02-15 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model's performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems.
Book Synopsis Hands-On Exploratory Data Analysis with Python by : Suresh Kumar Mukhiya
Download or read book Hands-On Exploratory Data Analysis with Python written by Suresh Kumar Mukhiya and published by Packt Publishing Ltd. This book was released on 2020-03-27 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover techniques to summarize the characteristics of your data using PyPlot, NumPy, SciPy, and pandas Key FeaturesUnderstand the fundamental concepts of exploratory data analysis using PythonFind missing values in your data and identify the correlation between different variablesPractice graphical exploratory analysis techniques using Matplotlib and the Seaborn Python packageBook Description Exploratory Data Analysis (EDA) is an approach to data analysis that involves the application of diverse techniques to gain insights into a dataset. This book will help you gain practical knowledge of the main pillars of EDA - data cleaning, data preparation, data exploration, and data visualization. You’ll start by performing EDA using open source datasets and perform simple to advanced analyses to turn data into meaningful insights. You’ll then learn various descriptive statistical techniques to describe the basic characteristics of data and progress to performing EDA on time-series data. As you advance, you’ll learn how to implement EDA techniques for model development and evaluation and build predictive models to visualize results. Using Python for data analysis, you’ll work with real-world datasets, understand data, summarize its characteristics, and visualize it for business intelligence. By the end of this EDA book, you’ll have developed the skills required to carry out a preliminary investigation on any dataset, yield insights into data, present your results with visual aids, and build a model that correctly predicts future outcomes. What you will learnImport, clean, and explore data to perform preliminary analysis using powerful Python packagesIdentify and transform erroneous data using different data wrangling techniquesExplore the use of multiple regression to describe non-linear relationshipsDiscover hypothesis testing and explore techniques of time-series analysisUnderstand and interpret results obtained from graphical analysisBuild, train, and optimize predictive models to estimate resultsPerform complex EDA techniques on open source datasetsWho this book is for This EDA book is for anyone interested in data analysis, especially students, statisticians, data analysts, and data scientists. The practical concepts presented in this book can be applied in various disciplines to enhance decision-making processes with data analysis and synthesis. Fundamental knowledge of Python programming and statistical concepts is all you need to get started with this book.
Book Synopsis R for Data Science by : Hadley Wickham
Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Book Synopsis Secondary Analysis of Electronic Health Records by : MIT Critical Data
Download or read book Secondary Analysis of Electronic Health Records written by MIT Critical Data and published by Springer. This book was released on 2016-09-09 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.
Book Synopsis Introduction to Optimization Methods and their Application in Statistics by : B. Everitt
Download or read book Introduction to Optimization Methods and their Application in Statistics written by B. Everitt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization techniques are used to find the values of a set of parameters which maximize or minimize some objective function of interest. Such methods have become of great importance in statistics for estimation, model fitting, etc. This text attempts to give a brief introduction to optimization methods and their use in several important areas of statistics. It does not pretend to provide either a complete treatment of optimization techniques or a comprehensive review of their application in statistics; such a review would, of course, require a volume several orders of magnitude larger than this since almost every issue of every statistics journal contains one or other paper which involves the application of an optimization method. It is hoped that the text will be useful to students on applied statistics courses and to researchers needing to use optimization techniques in a statistical context. Lastly, my thanks are due to Bertha Lakey for typing the manuscript.
Book Synopsis R and Data Mining by : Yanchang Zhao
Download or read book R and Data Mining written by Yanchang Zhao and published by Academic Press. This book was released on 2012-12-31 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. - Presents an introduction into using R for data mining applications, covering most popular data mining techniques - Provides code examples and data so that readers can easily learn the techniques - Features case studies in real-world applications to help readers apply the techniques in their work
Book Synopsis Advanced Methods in Biomedical Signal Processing and Analysis by : Kunal Pal
Download or read book Advanced Methods in Biomedical Signal Processing and Analysis written by Kunal Pal and published by Academic Press. This book was released on 2022-09-07 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques. - Gives advanced methods in signal processing - Includes machine and deep learning methods - Presents experimental case studies
Book Synopsis Sourcebook of Flavors by : Gary Reineccius
Download or read book Sourcebook of Flavors written by Gary Reineccius and published by Springer Science & Business Media. This book was released on 1994 with total page 952 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers all aspects of the flavor industry. Discusses mechanisms of flavor formation in plants and animal tissues; means of manufacturing flavors, including the handling and extraction of plant materials, liquid flavors, the creation of emulsions and dry flavorings; quality control, sensory analysis, sensory/instrumental correlations; safety of flavorings and legal considerations in the flavor industry. Features updated and expanded information on the role of the flavorist, uses of biotechnology for the production of flavoring material, essential oils, plant materials, and volatile and nonvolatile chemicals used in flavors, and a comprehensive list of flavoring ingredients and their legal status.
Book Synopsis Source book of flavors by : Gary Reineccius
Download or read book Source book of flavors written by Gary Reineccius and published by Springer Science & Business Media. This book was released on 2013-12-14 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt: Flavor is unquestionably one of the most extremely secretive one-reluctant to dis close anything that might be of value to a important attributes of the food we eat. competitor. Thus, little information about Man does not eat simply to live but even the activities of the flavor industry itself is more so lives to eat. Take away the pleasure offood and life becomes relatively mundane. available to the public. There now is a substantial body of liter The goal of the original Source Book of ature dealing with food flavor. The "golden Flavors, written by Henry Heath, was to years" of flavor research in the United States bring together in one volume as much of the were the 1960s and 70s. Numerous academic worldwide data and facts and as many flavor and government institutions had strong related subjects (e. g. , food colors) as was flavor programs and money was readily possible. Henry Heath added a wealth of available for flavor research. In the 1980s personal information on how the industry and 90s, research funding has become diffi accomplishes its various activities, which cult to obtain, particularly in an esthetic had never been published in any other liter area such as food flavor. The number of ature. It has been the intent of this author to research groups focusing on food flavor has update and build upon the original work of declined in the United States. Fortunately, Henry Heath.
Book Synopsis The Analysis of Categorical Data Using GLIM by : James K. Lindsey
Download or read book The Analysis of Categorical Data Using GLIM written by James K. Lindsey and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present text is the result of teaching a third year statistical course to undergraduate social science students. Besides their previous statistics courses, these students have had an introductory course in computer programming (FORTRAN, Pascal, or C) and courses in calculus and linear algebra, so that they may not be typical students of sociology. This course on the analysis of contingency tables has been given with all students in front of computer terminals, and, more recently, micro computers, working interactively with GLIM. Given the importance of the analysis of categorical data using log linear models within the overall body of models known as general linear models (GLMs) treated by GLIM, this book should be of interest to anyone, in any field, concerned with such applications. It should be suitable as a manual for applied statistics courses covering this subject. I assume that the reader has already a reasonably strong foundation in statistics, and specifically in dealing with the log-linearllogistic models. I also assume that he or of GLIM itself. In she has access to the GLIM manual and to an operational version other words, this book does not pretend to present either a complete introduction to the use of GLIM or an exposition of the statistical properties of log-linearllogistic models. For the former, I would recommend Healy (1988) and Aitkin et al (1989). Por the latter, many books already exist, of which I would especially recommend that of Pingleton (1984) in the present context.
Book Synopsis The SAGE Sourcebook of Advanced Data Analysis Methods for Communication Research by : Andrew F. Hayes
Download or read book The SAGE Sourcebook of Advanced Data Analysis Methods for Communication Research written by Andrew F. Hayes and published by SAGE. This book was released on 2008 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: A must-have volume for every communication researcher's library, The SAGE Sourcebook of Advanced Data Analysis Methods for Communication Research provides an introductory treatment of various advanced statistical methods applied to research in the field of communication. Written by authors who use these methods in their own research, each chapter gives a non-technical overview of what the method is and how it can be used to answer communication-related questions or aide the researcher dealing with difficult data problems. Students and faculty interested in diving into a new statistical topic—such as latent growth modeling, multilevel modeling, propensity scoring, or time series analysis—will find each chapter an excellent springboard for acquiring the background needed to jump into more advanced, technical readings.
Book Synopsis Statistical Data Analysis by : Milan Meloun
Download or read book Statistical Data Analysis written by Milan Meloun and published by Woodhead Publishing Limited. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, computer supported data analysis by statistical methods has been one of the fastest growth areas in chemometrics, biometrics and other related branches of natural, technical and social sciences. This has been strongly supported by the development of exploratory data analysis, testing assumptions about data, model and statistical methods and computer intensive techniques. This book presents a combination of individual topics with solved problems and a collection of experimental tasks. Methods suitable for extreme or small and large datasets are described. Presents a combination of individual topics in one complete volume featuring statistical analysis of univariate and multivariate data Interspersed throughout with solved problems and experimental tasks suitable for extreme or small and large datasets Features the interpretation of results based on the comprehensive information about data behaviour and validity of used assumptions
Book Synopsis Economic Surveys and Data Analysis CIRET Conference Proceedings, Paris 2000 by : OECD
Download or read book Economic Surveys and Data Analysis CIRET Conference Proceedings, Paris 2000 written by OECD and published by OECD Publishing. This book was released on 2002-12-17 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 25th CIRET Conference, entitled "Business Surveys and Empirical Analysis of Economic and Social Survey Data" was hosted by OECD and INSEE in Paris, France in 2000.
Book Synopsis Advanced Methods for Interpreting Geological and Geophysical Data by : Ahmed M. Eldosouky
Download or read book Advanced Methods for Interpreting Geological and Geophysical Data written by Ahmed M. Eldosouky and published by Frontiers Media SA. This book was released on 2024-07-08 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: The introduction and application of advanced geological and geophysical methods can solve many problems related to geoscience. This Research Topic gives a thorough treatment of the interpretation of geological and geophysical data through advanced techniques and integrated approaches. It aims to create a more reliable integration of various geological and geophysical data in an exploration and new findings context weighing the strengths and limitations of the various methods in order to develop geophysical and geological models. It will also focus on the interpretation techniques for evaluating structural and sedimentological (stratigraphical) processes with applications within resource exploration, geohazards, seismology, seabed ecology and global climate.
Book Synopsis Multivariate Data Analysis by : Fionn Murtagh
Download or read book Multivariate Data Analysis written by Fionn Murtagh and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in statistical methodology is increasing so rapidly in the astronomical community that accessible introductory material in this area is long overdue. This book fills the gap by providing a presentation of the most useful techniques in multivariate statistics. A wide-ranging annotated set of general and astronomical bibliographic references follows each chapter, providing valuable entry-points for research workers in all astronomical sub-disciplines. Although the applications considered focus on astronomy, the algorithms used can be applied to similar problems in other branches of science. Fortran programs are provided for many of the methods described.
Book Synopsis Quantitative Methods for Historians by : Konrad H. Jarausch
Download or read book Quantitative Methods for Historians written by Konrad H. Jarausch and published by UNC Press Books. This book was released on 2016-08-01 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The pioneering texts in quantitative history were written over two decades ago, but as a command of methodological context, computer experience, and statistical literacy have become increasingly important to the study of history, the need for an introductory text addressing these matters has increased. Quantitative Methods for Historians is a theoretical and practical guide for the application of quantitative analysis in historical research. It is designed for students of history and related disciplines who are curious about the possibilities of quantification and want to learn more about its recent development. Integrating the use of the statistical packages SAS and SPSS with the quantitative method, the authors discuss techniques for defining a problem, proceed to the building of a data set and the use of statistical methods, and conclude with the interpretation of results. The data set section concentrates on the basics of formalized research, discussing the coding process and the more complicated problems of data transformation and linkage. The statistical parts systematically build upon traditional fundamentals and introduce new analytical techniques for qualitative variables. Intended as a working introduction to quantitative methods, this guide also provides additional information on advanced statistical techniques and discusses questions of historical computing, reflecting critically on the proper role of quantitative methods.
