Download or read book LEARNING CAUSAL MODELS OF MULTIVARIATE SYSTEMS And the Value of it for the Performance Modeling of Computer Programs written by Jan Lemeire and published by ASP / VUBPRESS / UPA. This book was released on 2007 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Artificial Intelligence written by Ildar Batyrshin and published by Springer Science & Business Media. This book was released on 2011-11-14 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 7094 and LNAI 7095 constitutes the refereed proceedings of the 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, held in Puebla, Mexico, in November/December 2011. The 96 revised papers presented were carefully reviewed and selected from numerous submissions. The first volume includes 50 papers representing the current main topics of interest for the AI community and their applications. The papers are organized in the following topical sections: automated reasoning and multi-agent systems; problem solving and machine learning; natural language processing; robotics, planning and scheduling; and medical applications of artificial intelligence.
Download or read book Causality in the Sciences written by Phyllis McKay Illari and published by Oxford University Press. This book was released on 2011-03-17 with total page 953 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why do ideas of how mechanisms relate to causality and probability differ so much across the sciences? Can progress in understanding the tools of causal inference in some sciences lead to progress in others? This book tackles these questions and others concerning the use of causality in the sciences.
Download or read book Elements of Causal Inference written by Jonas Peters and published by MIT Press. This book was released on 2017-11-29 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.
Download or read book Education A E written by University Microfilms, Incorporated and published by University Microfilms. This book was released on 1989 with total page 796 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Cumulative Subject Index to Psychological Abstracts written by and published by . This book was released on 1969 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonrecursive Causal Models written by William Dale Berry and published by SAGE. This book was released on 1984-07 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author defines the concept of identification and explains what 'goes wrong' with some nonrecursive models to make them nonidentified. He provides various tests which can be used to determine whether a nonrecursive model is identified, and reviews common techniques for estimating the parameters of an identified model.
Download or read book Program Evaluation in the Health Fields written by Herbert C. Schulberg and published by . This book was released on 1970 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: In assembling almost three dozen papers which bear upon the evaluation of health programs, we have tried to select those materials which could meet the needs of both researchers and program directors. It is believed that in spite of the well-known differences in orientation and priorities which these two groups frequently exhibit, nevertheless there exists a wide span of common concern which needs only to be properly plumbed. To capitalize upon the mutual interests of researchers and practitioners and to demonstrate opportunities for fruitful collaboration, we have emphasized papers of potential interest to both groups and avoided selections which were overly skewed toward the needs of only one of them. Many other sources are available for the study of program development or research methodology but this volume one differs in its attempt to integrate what generally have been dichotomous fields of interest. Volume II was a response to the escalating demands for accountability, increasingly complex conceptual and methodological options, and a proliferating literature require that sophisticated materials be readily available if assessments are to be performed in knowledgeable ways. When is paired with our earlier volume, those teaching the growing number of program evaluation courses in medical schools and schools of public health, social work, and business should have more than enough reading materials for their introductory and advanced seminars.
Download or read book Causal Models in Experimental Designs written by H. M. Blalock and published by Routledge. This book was released on 2017-07-12 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a companion volume to Causal Models in the Social Sciences, the majority of articles concern panel designs involving repeated measurements while a smaller cluster involve discussions of how experimental designs may be improved by more explicit attention to causal models. All of the papers are concerned with complications that may occur in actual research designs- as compared with idealized ones that often become the basis of textbook discussions of design issues.
Download or read book Resources in Education written by and published by . This book was released on 1998 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1986 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Critical Essays in Music Education written by MarveleneC. Moore and published by Routledge. This book was released on 2017-07-05 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of essays references traditional and contemporary thought on theory and practice in music education for all age groups, from the very young to the elderly. The material spans a broad range of subject areas from history and philosophy to art and music, and addresses issues such as curriculum, pedagogy, assessment and evaluation, as well as current issues in technology and performance standards. Written by leading researchers and educators from diverse countries and cultures, this selection of previously published articles, research studies and book chapters is representative of the most frequently discussed and debated topics in the profession. This volume, which documents the importance of lifelong learning, is an indispensable reference work for specialists in the field of music education.
Download or read book ERIC Educational Documents Index written by Educational Resources Information Center (U.S.) and published by . This book was released on 1966 with total page 820 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A subject-author-institution index which provides titles and accession numbers to the document and report literature that was announced in the monthly issues of Resources in education" (earlier called Research in education).
Download or read book ERIC Educational Documents Index 1966 1969 Major descriptors written by CCM Information Corporation and published by . This book was released on 1970 with total page 818 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Bayesian Semiparametric Multivariate Causal Model with Automatic Covariate Selection and for Possibly Nonignorable Missing Data written by G. Karabatsos and published by . This book was released on 2010 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt: Causal inference is central to educational research, where in data analysis the aim is to learn the causal effects of educational treatments on academic achievement, to evaluate educational policies and practice. Compared to a correlational analysis, a causal analysis enables policymakers to make more meaningful statements about the efficacy of educational treatments. The fundamental problem of causal inference is that, at a given time, each subject can be exposed to only one of the treatments (Holland, 1986). Causal inference becomes inaccurate whenever data violate certain assumptions that are often made in practice, including: (1) the usual assumption of no outliers in the potential outcomes, (2) the typical assumptions that the treatment assignments have no outliers, no hidden bias (e.g., Rosenbaum, 2002), no confounding, and satisfy the Stable Unit Treatment Value Assumption (SUTVA; Cox, 1958); (3) the usual assumption that the missing data values are either missing-at-random (MAR) or missing-completely-at-random (MCAR) (Little & Rubin, 2002; Ibrahim, Chen, Lipsitz, & Herring, 2005), and (4) the usual assumption that parameter estimation requires no penalty for the absolute size of regression coefficients. To address the four open issues of causal modeling, the authors introduce a Bayesian semiparametric causal model, which provides a semiparametric approach to the full Rubin (1978) Causal Model. The paper presents their semiparametric causal model in full detail. The authors then illustrate this model through the analysis of data from the Progress In International Reading Literacy Study (PIRLS), to infer the causal effects of a writing instructional treatment on the reading performance of low-income students. This analysis is performed in a typical context of an observational study where SUTVA is potentially violated by the interference of subjects within each classroom, with many covariates describing the student, teacher, classroom, and school, where hidden bias and confounding can be present, and where there are missing covariate, treatment assignment, and potential outcome data, that can either be randomly (MCAR or MAR) or nonignorably missing. (Contains 3 tables and 3 figures.
Download or read book Assessing Students Digital Reading Performance written by Jie HU and published by Taylor & Francis. This book was released on 2022-12-30 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a systematic study of the Programme for International Student Assessment (PISA) based on big data analysis, aiming to examine the contextual factors relevant to students’ digital reading performance. The author first introduces the research landscape of educational data mining (EDM) and reviews the PISA framework since its launch and how it has become an important metric to assess the knowledge and skills of students from across the globe. With a focus on methodology and its applications, the book explores extant scholarship on the dynamic model of educational effectiveness, multi-level factors of digital reading performance, and the application of EDM approaches. The core chapter on the methodology examines machine learning algorithms, hierarchical linear modeling, mediation analysis, and data extraction and processing for the PISA dataset. The findings give insights into the influencing factors of students’ digital reading performance, allowing for further investigations on improving students’ digital reading literacy and more attention to the advancement of education effectiveness. The book will appeal to scholars, professionals, and policymakers interested in reading education, educational data mining, educational technology, and PISA, as well as students learning how to utilize machine learning algorithms in examining the mass global database.
Download or read book Causality and Causal Modelling in the Social Sciences written by Federica Russo and published by Springer Science & Business Media. This book was released on 2008-09-18 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus breaking down the dominant Human paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models. It is also shown to be latent – yet fundamental – in many philosophical accounts. Moreover, it has significant consequences for methodological issues: the warranty of the causal interpretation of causal models, the levels of causation, the characterisation of mechanisms, and the interpretation of probability. This book offers a novel philosophical and methodological approach to causal reasoning in causal modelling and provides the reader with the tools to be up to date about various issues causality rises in social science.
