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Author: Christoph Molnar
Publisher: Lulu.com
ISBN: 0244768528
Category : Computers
Languages : en
Pages : 320
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Book Description
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.
Author: Christoph Molnar
Publisher: Lulu.com
ISBN: 0244768528
Category : Computers
Languages : en
Pages : 320
Get Book Here
Book Description
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.
Author: Gyde Hansen
Publisher: John Benjamins Publishing
ISBN: 902729108X
Category : Language Arts & Disciplines
Languages : en
Pages : 317
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Book Description
This volume covers a wide range of topics in Interpreting and Translation Research. Some deal with scientometrics and the history of Interpreting Studies, arguments about conceptual analysis, meta-language and interpreters’ risk-taking strategies. Other papers are on research skills like career management, writing communicative abstracts and the practicalities of survey research. Several contributions address empirical issues such as expertise in Simultaneous Interpreting, the cognitive load imposed on interpreters by a non-native accent, the impact of intonation on interpreting quality, linguistic interference in Simultaneous Interpreting, similarities between translation and interpreting, and the relation between translation competence and revision competence. The collection is a tribute to Daniel Gile, in appreciation of his creativity and his commitment to interpreting and translation research. All the contributions in some way show his influence or are related to the models and research he has shaped.
Author: Michel R. V. Chaudron
Publisher: Springer
ISBN: 3642016480
Category : Computers
Languages : en
Pages : 413
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Book Description
This book constitutes a collection of the best papers selected from the 12 workshops and 3 tutorials held in conjunction with MODELS 2008, the 11th International Conference on Model Driven Engineering Languages and Systems, in Toulouse, France, September 28 - October 3, 2008. The contributions are organized within the volume according to the workshops at which they were presented: Model Based Architecting and Construction of Embedded Systems (ACES-MB); Challenges in Model Driven Software Engineering (CHAMDE); Empirical Studies of Model Driven Engineering (ESMDA); Models@runtime; Model Co-evolution and Consistency Management (MCCM); Model-Driven Web Engineering (MDWE); Modeling Security (MODSEC); Model-Based Design of Trustworthy Health Information Systems (MOTHIS); Non-functional System Properties in Domain Specific Modeling Languages (NFPin DSML); OCL Tools: From Implementation to Evaluation and Comparison (OCL); Quality in Modeling (QIM); and Transforming and Weaving Ontologies and Model Driven Engineering (TWOMDE). Each section includes a summary of the workshop. The last three sections contain selected papers from the Doctoral Symposium, the Educational Symposium and the Research Project Symposium, respectively.
Author: P. D. Magnus
Publisher:
ISBN:
Category : Logic
Languages : en
Pages : 0
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Book Description
Author: Benjamin M. Bolker
Publisher: Princeton University Press
ISBN: 0691125228
Category : Computers
Languages : en
Pages : 408
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Book Description
Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.
Author: Alvin C. Rencher
Publisher: John Wiley & Sons
ISBN: 0470192607
Category : Mathematics
Languages : en
Pages : 690
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Book Description
The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.
Author: Mogens Myrup Andreasen
Publisher: Springer
ISBN: 3319198394
Category : Technology & Engineering
Languages : en
Pages : 400
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Book Description
Maximising reader insights into the theory, models, methods and fundamental reasoning of design, this book addresses design activities in industrial settings, as well as the actors involved. This approach offers readers a new understanding of design activities and related functions, properties and dispositions. Presenting a ‘design mindset’ that seeks to empower students, researchers, and practitioners alike, it features a strong focus on how designers create new concepts to be developed into products, and how they generate new business and satisfy human needs. Employing a multi-faceted perspective, the book supplies the reader with a comprehensive worldview of design in the form of a proposed model that will empower their activities as student, researcher or practitioner. We draw the reader into the core role of design conceptualisation for society, for the development of industry, for users and buyers of products, and for citizens in relation to public systems. The book also features original contributions related to exploration, conceptualisation and product synthesis. Exploring both the power and limitations of formal design process models, methods, and tools viewed in the light of human ingenuity and cognition, the book develops a unique design mindset that adds human understanding to the list of methods and tools essential to design. This insight is distilled into useful mindset heuristics included throughout the book.
Author: Sue L. T. McGregor
Publisher: SAGE Publications
ISBN: 1506350976
Category : Social Science
Languages : en
Pages : 880
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Book Description
Understanding and Evaluating Research: A Critical Guide shows students how to be critical consumers of research and to appreciate the power of methodology as it shapes the research question, the use of theory in the study, the methods used, and how the outcomes are reported. The book starts with what it means to be a critical and uncritical reader of research, followed by a detailed chapter on methodology, and then proceeds to a discussion of each component of a research article as it is informed by the methodology. The book encourages readers to select an article from their discipline, learning along the way how to assess each component of the article and come to a judgment of its rigor or quality as a scholarly report.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309287812
Category : Mathematics
Languages : en
Pages : 191
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Book Description
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Author: Sandip Banerjee
Publisher: CRC Press
ISBN: 1351022938
Category : Mathematics
Languages : en
Pages : 419
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Book Description
Mathematical Modeling: Models, Analysis and Applications, Second Edition introduces models of both discrete and continuous systems. This book is aimed at newcomers who desires to learn mathematical modeling, especially students taking a first course in the subject. Beginning with the step-by-step guidance of model formulation, this book equips the reader about modeling with difference equations (discrete models), ODE’s, PDE’s, delay and stochastic differential equations (continuous models). This book provides interdisciplinary and integrative overview of mathematical modeling, making it a complete textbook for a wide audience. A unique feature of the book is the breadth of coverage of different examples on mathematical modelling, which include population models, economic models, arms race models, combat models, learning model, alcohol dynamics model, carbon dating, drug distribution models, mechanical oscillation models, epidemic models, tumor models, traffic flow models, crime flow models, spatial models, football team performance model, breathing model, two neuron system model, zombie model and model on love affairs. Common themes such as equilibrium points, stability, phase plane analysis, bifurcations, limit cycles, period doubling and chaos run through several chapters and their interpretations in the context of the model have been highlighted. In chapter 3, a section on estimation of system parameters with real life data for model validation has also been discussed. Features Covers discrete, continuous, spatial, delayed and stochastic models. Over 250 illustrations, 300 examples and exercises with complete solutions. Incorporates MATHEMATICA® and MATLAB®, each chapter contains Mathematica and Matlab codes used to display numerical results (available at CRC website). Separate sections for Projects. Several exercise problems can also be used for projects. Presents real life examples of discrete and continuous scenarios. The book is ideal for an introductory course for undergraduate and graduate students, engineers, applied mathematicians and researchers working in various areas of natural and applied sciences.
