Interpretable Machine Learning

Interpretable Machine Learning PDF 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.

Interpretable Machine Learning

Interpretable Machine Learning PDF 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.

Efforts and Models in Interpreting and Translation Research

Efforts and Models in Interpreting and Translation Research PDF 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.

Introduction to the Foundations of Mathematics

Introduction to the Foundations of Mathematics PDF Author: Raymond L. Wilder
Publisher: Courier Corporation
ISBN: 0486276201
Category : Mathematics
Languages : en
Pages : 354

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Book Description
Classic undergraduate text acquaints students with fundamental concepts and methods of mathematics. Topics include axiomatic method, set theory, infinite sets, groups, intuitionism, formal systems, mathematical logic, and much more. 1965 second edition.

Empirical modelling of translation and interpreting

Empirical modelling of translation and interpreting PDF Author: Hansen-Schirra, Silvia
Publisher: Language Science Press
ISBN: 3961100241
Category : Corpora (Linguistics)
Languages : en
Pages : 522

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Book Description
Empirical research is carried out in a cyclic way: approaching a research area bottom-up, data lead to interpretations and ideally to the abstraction of laws, on the basis of which a theory can be derived. Deductive research is based on a theory, on the basis of which hypotheses can be formulated and tested against the background of empirical data. Looking at the state-of-the-art in translation studies, either theories as well as models are designed or empirical data are collected and interpreted. However, the final step is still lacking: so far, empirical data has not lead to the formulation of theories or models, whereas existing theories and models have not yet been comprehensively tested with empirical methods. This publication addresses these issues from several perspectives: multi-method product- as well as process-based research may gain insights into translation as well as interpreting phenomena. These phenomena may include cognitive and organizational processes, procedures and strategies, competence and performance, translation properties and universals, etc. Empirical findings about the deeper structures of translation and interpreting will reduce the gap between translation and interpreting practice and model and theory building. Furthermore, the availability of more large-scale empirical testing triggers the development of models and theories concerning translation and interpreting phenomena and behavior based on quantifiable, replicable and transparent data.

Models in Software Engineering

Models in Software Engineering PDF 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.

Forall X

Forall X PDF Author: P. D. Magnus
Publisher:
ISBN:
Category : Logic
Languages : en
Pages : 0

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Book Description


Data Analysis Using Regression and Multilevel/Hierarchical Models

Data Analysis Using Regression and Multilevel/Hierarchical Models PDF Author: Andrew Gelman
Publisher: Cambridge University Press
ISBN: 9780521686891
Category : Mathematics
Languages : en
Pages : 654

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Book Description
This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Ecological Models and Data in R

Ecological Models and Data in R PDF 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.

Conceptual Design

Conceptual Design PDF 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.

Mixed Effects Models for Complex Data

Mixed Effects Models for Complex Data PDF Author: Lang Wu
Publisher: CRC Press
ISBN: 9781420074086
Category : Mathematics
Languages : en
Pages : 431

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Book Description
Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.