This book offers a thorough overview of the most popular and researched meta-heuristic optimization techniques and nature-inspired algorithms. Their wide applicability makes them a hot research topic and an effi cient tool for the solution of complex optimization problems in various fi elds of sciences, engineering, and in numerous industries.
Metal Studies is a "booming" research field that has gained tremendous momentum in recent years. In this field, Heavy Metal is studied both as a cultural practice and as a musical genre. However, many of the most urgent conceptual questions have remained unanswered - especially those that lie outside the research interests of the founding disciplines of Metal Studies. This first volume of the book series "Meta/Metal" tries to answer some of these questions. The book brings together contributions by leading scholars and young experts, each of which responds to one of the conceptual desiderata that have so far arisen in Metal Studies. All contributions share a commitment to combining basic research with empirical accuracy in this research field.
The book focuses on different variants of decision tree induction but also describes the meta-learning approach in general which is applicable to other types of machine learning algorithms. The book discusses different variants of decision tree induction and represents a useful source of information to readers wishing to review some of the techniques used in decision tree learning, as well as different ensemble methods that involve decision trees. It is shown that the knowledge of different components used within decision tree learning needs to be systematized to enable the system to generate and evaluate different variants of machine learning algorithms with the aim of identifying the top-most performers or potentially the best one. A unified view of decision tree learning enables to emulate different decision tree algorithms simply by setting certain parameters. As meta-learning requires running many different processes with the aim of obtaining performance results, a detailed description of the experimental methodology and evaluation framework is provided. Meta-learning is discussed in great detail in the second half of the book. The exposition starts by presenting a comprehensive review of many meta-learning approaches explored in the past described in literature, including for instance approaches that provide a ranking of algorithms. The approach described can be related to other work that exploits planning whose aim is to construct data mining workflows. The book stimulates interchange of ideas between different, albeit related, approaches.
This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. As such, the book introduces the key concepts and models used in meta-analysis. It also includes chapters on the following advanced topics: publication bias and small study effects; missing data; multivariate meta-analysis, network meta-analysis; and meta-analysis of diagnostic studies.
Metaphysical theories are beautiful. At the end of this book, Jiri Benovsky defends the view that metaphysical theories possess aesthetic properties and that these play a crucial role when it comes to theory evaluation and theory choice.Before we get there, the philosophical path the author proposes to follow starts with three discussions of metaphysical equivalence. Benovsky argues that there are cases of metaphysical equivalence, cases of partial metaphysical equivalence, as well as interesting cases of theories that are not equivalent. Thus, claims of metaphysical equivalence can only be raised locally. The slogan is: the best way to do meta-metaphysics is to do first-level metaphysics.To do this work, Benovsky focuses on the nature of primitives and on the role they play in each of the theories involved. He emphasizes the utmost importance of primitives in the construction of metaphysical theories and in the subsequent evaluation of them.He then raises the simple but complicated question: how to make a choice between competing metaphysical theories? If two theories are equivalent, then perhaps we do not need to make a choice. But what about all the other cases of non-equivalent "equally good" theories? Benovsky uses some of the theories discussed in the first part of the book as examples and examines some traditional meta-theoretical criteria for theory choice (various kinds of simplicity, compatibility with physics, compatibility with intuitions, explanatory power, internal consistency,...) only to show that they do not allow us to make a choice.But if the standard meta-theoretical criteria cannot help us in deciding between competing non-equivalent metaphysical theories, how then shall we make that choice? This is where Benovsky argues that metaphysical theories possess aesthetic properties – grounded in non-aesthetic properties – and that these play a crucial role in theory choice and evaluation. This view, as well as allthe meta-metaphysical considerations discussed throughout the book, then naturally lead the author to a form of anti-realism, and at the end of the journey he offers reasons to think better of the kind of anti-realist view he proposes to embrace.www.jiribenovsky.org
This volume offers a meta-philosophical reflection on feminist philosophies of science. It emphasizes and discusses both the connections and differences between "traditional" philosophies of science and feminist philosophies of science. The collection systematically analyses feminist contributions to the various philosophies of specific sciences. Each chapter is devoted to a specific area of philosophy of science: general philosophy of science, philosophy of biology, philosophy of climate sciences, philosophy of cognitive sciences and neurosciences, philosophy of economics, philosophy of history and archaeology, philosophy of logic and mathematics, philosophy of medicine, philosophy of psychology, philosophy of physics, and philosophy of social sciences. Since some of these areas have so far rarely been addressed by feminist philosophers, this new collection provides new angels and stimulates the debate on pivotal issues that are part and parcel of both "traditional" philosophies of science and feminist philosophies of science. Using a range of different methodologies and styles, the essays all show great clarity in both arguments and contents.
This book explains how to employ MASEM, the combination of meta-analysis (MA) and structural equation modelling (SEM). It shows how by using MASEM, a single model can be tested to explain the relationships between a set of variables in several studies. This book gives an introduction to MASEM, with a focus on the state of the art approach: the two stage approach of Cheung and Cheung & Chan. Both, the fixed and the random approach to MASEM are illustrated with two applications to real data. All steps that have to be taken to perform the analyses are discussed extensively. All data and syntax files are available online, so that readers can imitate all analyses. By using SEM for meta-analysis, this book shows how to benefit from all available information from all available studies, even if few or none of the studies report about all relationships that feature in the full model of interest.
