Author: Timothy Nathaniel Rubin
Publisher:
ISBN: 9781267782403
Category :
Languages : en
Pages : 102
Book Description
There is substantial overlap between categorization research in psychology and classification research in machine learning and statistics. I will first discuss the relationship between these two areas and present a framework that illuminates the contexts in which the aims of these two fields become functionally equivalent. I will then present work from both areas that illustrates some ways in which the fields can learn from one another. First, I will present research on document classification using a "multilabel" representational system, in which each document is assigned to one or more non-disjoint classes. I will then present research in which similar representations are applied to model hierarchical categories from the animal domain in humans.
Categorization and Classification in Machine Learning and Psychology
Author: Timothy Nathaniel Rubin
Publisher:
ISBN: 9781267782403
Category :
Languages : en
Pages : 102
Book Description
There is substantial overlap between categorization research in psychology and classification research in machine learning and statistics. I will first discuss the relationship between these two areas and present a framework that illuminates the contexts in which the aims of these two fields become functionally equivalent. I will then present work from both areas that illustrates some ways in which the fields can learn from one another. First, I will present research on document classification using a "multilabel" representational system, in which each document is assigned to one or more non-disjoint classes. I will then present research in which similar representations are applied to model hierarchical categories from the animal domain in humans.
Publisher:
ISBN: 9781267782403
Category :
Languages : en
Pages : 102
Book Description
There is substantial overlap between categorization research in psychology and classification research in machine learning and statistics. I will first discuss the relationship between these two areas and present a framework that illuminates the contexts in which the aims of these two fields become functionally equivalent. I will then present work from both areas that illustrates some ways in which the fields can learn from one another. First, I will present research on document classification using a "multilabel" representational system, in which each document is assigned to one or more non-disjoint classes. I will then present research in which similar representations are applied to model hierarchical categories from the animal domain in humans.
Categorization by Humans and Machines
Author:
Publisher: Academic Press
ISBN: 0080863809
Category : Computers
Languages : en
Pages : 573
Book Description
The objective of the series has always been to provide a forum in which leading contributors to an area can write about significant bodies of research in which they are involved. The operating procedure has been to invite contributions from interesting, active investigators, and then allow them essentially free rein to present their perspectives on important research problems. The result of such invitations over the past two decades has been collections of papers which consist of thoughtful integrations providing an overview of a particular scientific problem. The series has an excellent tradition of high quality papers and is widely read by researchers in cognitive and experimental psychology.
Publisher: Academic Press
ISBN: 0080863809
Category : Computers
Languages : en
Pages : 573
Book Description
The objective of the series has always been to provide a forum in which leading contributors to an area can write about significant bodies of research in which they are involved. The operating procedure has been to invite contributions from interesting, active investigators, and then allow them essentially free rein to present their perspectives on important research problems. The result of such invitations over the past two decades has been collections of papers which consist of thoughtful integrations providing an overview of a particular scientific problem. The series has an excellent tradition of high quality papers and is widely read by researchers in cognitive and experimental psychology.
Formal Approaches in Categorization
Author: Emmanuel M. Pothos
Publisher: Cambridge University Press
ISBN: 1139493973
Category : Psychology
Languages : en
Pages : 349
Book Description
The process of constructing concepts underpins our capacity to encode information in an efficient and competent manner and also, ultimately, our ability to think in terms of abstract ideas such as justice, love and happiness. But what are the mechanisms which correspond to psychological categorization processes? This book unites many prominent approaches in modelling categorization. Each chapter focuses on a particular formal approach to categorization, presented by the proponent(s) or advocate(s) of that approach, and the authors consider the relation of this approach to other models and the ultimate objectives in their research programmes. The volume evaluates progress that has been made in the field and where it goes from here. This is an essential companion to any scientist interested in the formal description of categorization and, more generally, in formal approaches to cognition. It will be the definitive guide to formal approaches in categorization research for years to come.
Publisher: Cambridge University Press
ISBN: 1139493973
Category : Psychology
Languages : en
Pages : 349
Book Description
The process of constructing concepts underpins our capacity to encode information in an efficient and competent manner and also, ultimately, our ability to think in terms of abstract ideas such as justice, love and happiness. But what are the mechanisms which correspond to psychological categorization processes? This book unites many prominent approaches in modelling categorization. Each chapter focuses on a particular formal approach to categorization, presented by the proponent(s) or advocate(s) of that approach, and the authors consider the relation of this approach to other models and the ultimate objectives in their research programmes. The volume evaluates progress that has been made in the field and where it goes from here. This is an essential companion to any scientist interested in the formal description of categorization and, more generally, in formal approaches to cognition. It will be the definitive guide to formal approaches in categorization research for years to come.
Classification and Cognition
Author: William K. Estes
Publisher: Oxford University Press
ISBN: 0195360885
Category : Psychology
Languages : en
Pages : 298
Book Description
Based on Estes' important Fitts Lectures, this volume details a set of psychological concepts and principles that offers a unified interpretation of a wide variety of memory, categorization, and decision-making phenomena. These phenomena are explained via two families of models established by the author: a storage-retrieval model and an adaptive network model. Estes considers whether the models are competing or complementary, offering cogent and instructive arguments for both perspectives. Estes' theory is then applied to two large-scale series of studies on category learning and recognition, providing an integrated understanding of seemingly disparate phenomena. This book is the culmination of the author's more than ten years of research in the field, and stands as a great achievement by one of this century's eminent psychologists. It will be indispensable to a wide variety of behavioral scientists, including mathematical and cognitive psychologists.
Publisher: Oxford University Press
ISBN: 0195360885
Category : Psychology
Languages : en
Pages : 298
Book Description
Based on Estes' important Fitts Lectures, this volume details a set of psychological concepts and principles that offers a unified interpretation of a wide variety of memory, categorization, and decision-making phenomena. These phenomena are explained via two families of models established by the author: a storage-retrieval model and an adaptive network model. Estes considers whether the models are competing or complementary, offering cogent and instructive arguments for both perspectives. Estes' theory is then applied to two large-scale series of studies on category learning and recognition, providing an integrated understanding of seemingly disparate phenomena. This book is the culmination of the author's more than ten years of research in the field, and stands as a great achievement by one of this century's eminent psychologists. It will be indispensable to a wide variety of behavioral scientists, including mathematical and cognitive psychologists.
Classification in the Wild
Author: Konstantinos V. Katsikopoulos
Publisher: MIT Press
ISBN: 0262361957
Category : Language Arts & Disciplines
Languages : en
Pages : 208
Book Description
Rules for building formal models that use fast-and-frugal heuristics, extending the psychological study of classification to the real world of uncertainty. This book focuses on classification--allocating objects into categories--"in the wild," in real-world situations and far from the certainty of the lab. In the wild, unlike in typical psychological experiments, the future is not knowable and uncertainty cannot be meaningfully reduced to probability. Connecting the science of heuristics with machine learning, the book shows how to create formal models using classification rules that are simple, fast, and transparent and that can be as accurate as mathematically sophisticated algorithms developed for machine learning.
Publisher: MIT Press
ISBN: 0262361957
Category : Language Arts & Disciplines
Languages : en
Pages : 208
Book Description
Rules for building formal models that use fast-and-frugal heuristics, extending the psychological study of classification to the real world of uncertainty. This book focuses on classification--allocating objects into categories--"in the wild," in real-world situations and far from the certainty of the lab. In the wild, unlike in typical psychological experiments, the future is not knowable and uncertainty cannot be meaningfully reduced to probability. Connecting the science of heuristics with machine learning, the book shows how to create formal models using classification rules that are simple, fast, and transparent and that can be as accurate as mathematically sophisticated algorithms developed for machine learning.
Categories and Concepts
Author: Iven van Mechelen
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 394
Book Description
A book aimed at advanced undergraduates and graduates in cognitive science and artificial intelligence, linguistics, applied mathematics and data analysis.
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 394
Book Description
A book aimed at advanced undergraduates and graduates in cognitive science and artificial intelligence, linguistics, applied mathematics and data analysis.
Concept Formation
Author: Douglas H. Fisher
Publisher: Morgan Kaufmann
ISBN: 1483221164
Category : Computers
Languages : en
Pages : 489
Book Description
Concept Formation: Knowledge and Experience in Unsupervised Learning presents the interdisciplinary interaction between machine learning and cognitive psychology on unsupervised incremental methods. This book focuses on measures of similarity, strategies for robust incremental learning, and the psychological consistency of various approaches. Organized into three parts encompassing 15 chapters, this book begins with an overview of inductive concept learning in machine learning and psychology, with emphasis on issues that distinguish concept formation from more prevalent supervised methods and from numeric and conceptual clustering. This text then describes the cognitive consistency of two concept formation systems that are motivated by a rational analysis of human behavior relative to a variety of psychological phenomena. Other chapters consider the merits of various schemes for representing and acquiring knowledge during concept formation. This book discusses as well the earliest work in concept formation. The final chapter deals with acquisition of quantity conservation in developmental psychology. This book is a valuable resource for psychologists and cognitive scientists.
Publisher: Morgan Kaufmann
ISBN: 1483221164
Category : Computers
Languages : en
Pages : 489
Book Description
Concept Formation: Knowledge and Experience in Unsupervised Learning presents the interdisciplinary interaction between machine learning and cognitive psychology on unsupervised incremental methods. This book focuses on measures of similarity, strategies for robust incremental learning, and the psychological consistency of various approaches. Organized into three parts encompassing 15 chapters, this book begins with an overview of inductive concept learning in machine learning and psychology, with emphasis on issues that distinguish concept formation from more prevalent supervised methods and from numeric and conceptual clustering. This text then describes the cognitive consistency of two concept formation systems that are motivated by a rational analysis of human behavior relative to a variety of psychological phenomena. Other chapters consider the merits of various schemes for representing and acquiring knowledge during concept formation. This book discusses as well the earliest work in concept formation. The final chapter deals with acquisition of quantity conservation in developmental psychology. This book is a valuable resource for psychologists and cognitive scientists.
The Cambridge Handbook of Computational Psychology
Author: Ron Sun
Publisher: Cambridge University Press
ISBN: 0521674107
Category : Computers
Languages : en
Pages : 767
Book Description
A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.
Publisher: Cambridge University Press
ISBN: 0521674107
Category : Computers
Languages : en
Pages : 767
Book Description
A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.
Using Machine Learning to Understand and Influence Human Categorization Behavior
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 220
Book Description
In both machine learning (ML) and cognitive psychology (CP), categorization is considered a basic task commonly encountered by learning agents and studied in both fields. While a great deal of work in CP has been applied to understanding human learning in supervised categorization, little work has been done previously to investigate the effects of both labeled and unlabeled data as in the semi-supervised setting. I have had the opportunity to contribute to a number of studies investigating just this situation: human learners tasked with learning a categorization task from some combination of labeled and unlabeled data. This work has involved the use of ML to both (1) better understand how labeled and unlabeled data affect human learners in categorization tasks as well as (2) attempt to influence the resulting behavior using ideas and techniques derived from ML. The results of this work have shown that (1) in addition to humans being affected by the distribution of unlabeled data, they can also be affected by ordering of the unlabeled items (2) that humans are not constrained in their search of a parameter space when attempting to integrate new unlabeled items with previously labeled experience (3) that humans can learn using underlying manifold structure (4) that the speed of human learning on a supervised task can be affected by prior unlabeled experience and (5) that, using Co-Training constraints, human collaborators can be induced to learn a boundary neither would have likely learned on their own.
Publisher:
ISBN:
Category :
Languages : en
Pages : 220
Book Description
In both machine learning (ML) and cognitive psychology (CP), categorization is considered a basic task commonly encountered by learning agents and studied in both fields. While a great deal of work in CP has been applied to understanding human learning in supervised categorization, little work has been done previously to investigate the effects of both labeled and unlabeled data as in the semi-supervised setting. I have had the opportunity to contribute to a number of studies investigating just this situation: human learners tasked with learning a categorization task from some combination of labeled and unlabeled data. This work has involved the use of ML to both (1) better understand how labeled and unlabeled data affect human learners in categorization tasks as well as (2) attempt to influence the resulting behavior using ideas and techniques derived from ML. The results of this work have shown that (1) in addition to humans being affected by the distribution of unlabeled data, they can also be affected by ordering of the unlabeled items (2) that humans are not constrained in their search of a parameter space when attempting to integrate new unlabeled items with previously labeled experience (3) that humans can learn using underlying manifold structure (4) that the speed of human learning on a supervised task can be affected by prior unlabeled experience and (5) that, using Co-Training constraints, human collaborators can be induced to learn a boundary neither would have likely learned on their own.
Handbook of Categorization in Cognitive Science
Author: Henri Cohen
Publisher: Elsevier
ISBN: 008045741X
Category : Psychology
Languages : en
Pages : 1136
Book Description
Categorization, the basic cognitive process of arranging objects into categories, is a fundamental process in human and machine intelligence and is central to investigations and research in cognitive science. Until now, categorization has been approached from singular disciplinary perspectives with little overlap or communication between the disciplines involved (Linguistics, Psychology, Philosophy, Neuroscience, Computer Science, Cognitive Anthropology). Henri Cohen and Claire Lefebvre have gathered together a stellar collection of contributors in this unique, ambitious attempt to bring together converging disciplinary and conceptual perspectives on this topic. "Categorization is a key concept across the range of cognitive sciences, including linguistics and philosophy, yet hitherto it has been hard to find accounts that go beyond the concerns of one or two individual disciplines. The Handbook of Categorization in Cognitive Science provides just the sort of interdisciplinary approach that is necessary to synthesize knowledge from the different fields and provide the basis for future innovation." Professor Bernard Comrie, Department of Linguistics, Max Planck Institute for Evolutionary Anthropology, Germany "Anyone concerned with language, semantics, or categorization will want to have this encyclopedic collection." Professor Eleanor Rosch, Dept of Psychology, University of California, Berkeley, USA
Publisher: Elsevier
ISBN: 008045741X
Category : Psychology
Languages : en
Pages : 1136
Book Description
Categorization, the basic cognitive process of arranging objects into categories, is a fundamental process in human and machine intelligence and is central to investigations and research in cognitive science. Until now, categorization has been approached from singular disciplinary perspectives with little overlap or communication between the disciplines involved (Linguistics, Psychology, Philosophy, Neuroscience, Computer Science, Cognitive Anthropology). Henri Cohen and Claire Lefebvre have gathered together a stellar collection of contributors in this unique, ambitious attempt to bring together converging disciplinary and conceptual perspectives on this topic. "Categorization is a key concept across the range of cognitive sciences, including linguistics and philosophy, yet hitherto it has been hard to find accounts that go beyond the concerns of one or two individual disciplines. The Handbook of Categorization in Cognitive Science provides just the sort of interdisciplinary approach that is necessary to synthesize knowledge from the different fields and provide the basis for future innovation." Professor Bernard Comrie, Department of Linguistics, Max Planck Institute for Evolutionary Anthropology, Germany "Anyone concerned with language, semantics, or categorization will want to have this encyclopedic collection." Professor Eleanor Rosch, Dept of Psychology, University of California, Berkeley, USA