Logistic Regression Inside And Out

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Logistic Regression Inside And Out
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Author : Jeffrey Strickland
language : en
Publisher: Lulu.com
Release Date : 2017-03-13
Logistic Regression Inside And Out written by Jeffrey Strickland and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-13 with Business & Economics categories.
If you have a yes or no question, then you can probably answer it with a logistic regression model. Logistic regression is most appropriate when the dependent variable has two possible outcomes. Will customers respond to an offer or unsubscribe, will the enemy fight or flee, will subjects respond to treatment or grow ill, will livestock live or die? Yes or no? I am often asked if logistic regression is a machine learning algorithm. I say that it is not, for I can formulate it mathematically and solve it using matrix equations, for example. Its solution is derived deterministically, and estimation is performed mathematically, through optimization methods. The logit link functionis the mathematical expression-a nonlinear, exponential equation, and we transform it to a linear equation by applying the natural logarithm. Here we find mathematical modeling, probability, and statistics. Here I will take you on a journey into the art and science of predictive modeling using logistic regression, inside-and-out.
Best Practices In Logistic Regression
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Author : Jason W. Osborne
language : en
Publisher: SAGE Publications
Release Date : 2014-02-26
Best Practices In Logistic Regression written by Jason W. Osborne and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-26 with Social Science categories.
Jason W. Osborne’s Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers’ basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne’s applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension.
Interpretable Machine Learning
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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020
Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Logistic Regression
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Author : Scott W. Menard
language : en
Publisher: SAGE
Release Date : 2010
Logistic Regression written by Scott W. Menard and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.
Logistic Regression is designed for readers who have a background in statistics at least up to multiple linear regression, who want to analyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally.
Regression Inside Out
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Author : Eric W. Schoon
language : en
Publisher: Cambridge University Press
Release Date : 2024-02-22
Regression Inside Out written by Eric W. Schoon and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-22 with Mathematics categories.
Demonstrates new ways to extract knowledge from statistical data and unlock more nuanced interpretations than has previously been possible.
Applied Logistic Regression Analysis
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Author : Scott Menard
language : en
Publisher: SAGE Publications, Incorporated
Release Date : 1995-06-29
Applied Logistic Regression Analysis written by Scott Menard and has been published by SAGE Publications, Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995-06-29 with Mathematics categories.
Emphasizing the parallels between linear and logistic regression, Scott Menard explores logistic regression analysis and demonstrates its usefulness in analyzing dichotomous, polytomous nominal, and polytomous ordinal dependent variables. The book is aimed at readers with a background in bivariate and multiple linear regression.
Best Practices In Logistic Regression
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Author : Jason W. Osborne
language : en
Publisher: SAGE Publications
Release Date : 2014-02-26
Best Practices In Logistic Regression written by Jason W. Osborne and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-26 with Social Science categories.
Jason W. Osborne’s Best Practices in Logistic Regression provides students with an accessible, applied approach that communicates logistic regression in clear and concise terms. The book effectively leverages readers’ basic intuitive understanding of simple and multiple regression to guide them into a sophisticated mastery of logistic regression. Osborne’s applied approach offers students and instructors a clear perspective, elucidated through practical and engaging tools that encourage student comprehension. Best Practices in Logistic Regression explains logistic regression in a concise and simple manner that gives students the clarity they need without the extra weight of longer, high-level texts.
Best Practices In Quantitative Methods
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Author : Jason W. Osborne
language : en
Publisher: SAGE
Release Date : 2008
Best Practices In Quantitative Methods written by Jason W. Osborne and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Language Arts & Disciplines categories.
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
21st Century Sociology A Reference Handbook
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Author : Clifton D. Bryant
language : en
Publisher: SAGE
Release Date : 2007
21st Century Sociology A Reference Handbook written by Clifton D. Bryant and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Social Science categories.
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Applied Logistic Regression
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Author : David W. Hosmer, Jr.
language : en
Publisher: John Wiley & Sons
Release Date : 2004-10-28
Applied Logistic Regression written by David W. Hosmer, Jr. 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 2004-10-28 with Mathematics categories.
From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references." —Choice "Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent." —Contemporary Sociology "An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical." —The Statistician In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.