Calculus of thought neuromorphic logistic regression in cognitive machines Libro electrónico

Calculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus Ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems. The reduced error logistic regression (RELR) method is proposed as such a "Calculus of Thought." This book reviews how RELRs completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELRs new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today's big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior. *Provides a high-level introduction and detailed reviews of the neural, statistical and machine learning knowledge base as a foundation for a new era of smarter machines. *Argues that smarter machine learning to handle both explanation and prediction without cognitive bias must have a foundation in cognitive neuroscience and must embody similar explicit and implicit learning principles that occur in the brain. *Offers a new neuromorphic foundation for machine learning based upon the reduced error logistic regression (RELR) method and provides simple examples of RELR computations in toy problems that can be accessed in spreadsheet workbooks through a companion website.

Saved in:
Bibliographic Details
Main Author: Rice, Daniel M. autor/a
Format: Texto biblioteca
Language:eng
Published: Waltham, Massachusetts, United States Academic Press c201
Subjects:Computational neuroscience, Cognitive science,
Online Access:http://www.sciencedirect.com/science/book/9780124104075
Tags: Add Tag
No Tags, Be the first to tag this record!
id KOHA-OAI-ECOSUR:54714
record_format koha
institution ECOSUR
collection Koha
country México
countrycode MX
component Bibliográfico
access En linea
En linea
databasecode cat-ecosur
tag biblioteca
region America del Norte
libraryname Sistema de Información Bibliotecario de ECOSUR (SIBE)
language eng
topic Computational neuroscience
Cognitive science
Computational neuroscience
Cognitive science
spellingShingle Computational neuroscience
Cognitive science
Computational neuroscience
Cognitive science
Rice, Daniel M. autor/a
Calculus of thought neuromorphic logistic regression in cognitive machines Libro electrónico
description Calculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus Ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems. The reduced error logistic regression (RELR) method is proposed as such a "Calculus of Thought." This book reviews how RELRs completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELRs new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today's big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior. *Provides a high-level introduction and detailed reviews of the neural, statistical and machine learning knowledge base as a foundation for a new era of smarter machines. *Argues that smarter machine learning to handle both explanation and prediction without cognitive bias must have a foundation in cognitive neuroscience and must embody similar explicit and implicit learning principles that occur in the brain. *Offers a new neuromorphic foundation for machine learning based upon the reduced error logistic regression (RELR) method and provides simple examples of RELR computations in toy problems that can be accessed in spreadsheet workbooks through a companion website.
format Texto
topic_facet Computational neuroscience
Cognitive science
author Rice, Daniel M. autor/a
author_facet Rice, Daniel M. autor/a
author_sort Rice, Daniel M. autor/a
title Calculus of thought neuromorphic logistic regression in cognitive machines Libro electrónico
title_short Calculus of thought neuromorphic logistic regression in cognitive machines Libro electrónico
title_full Calculus of thought neuromorphic logistic regression in cognitive machines Libro electrónico
title_fullStr Calculus of thought neuromorphic logistic regression in cognitive machines Libro electrónico
title_full_unstemmed Calculus of thought neuromorphic logistic regression in cognitive machines Libro electrónico
title_sort calculus of thought neuromorphic logistic regression in cognitive machines libro electrónico
publisher Waltham, Massachusetts, United States Academic Press
publishDate c201
url http://www.sciencedirect.com/science/book/9780124104075
work_keys_str_mv AT ricedanielmautora calculusofthoughtneuromorphiclogisticregressionincognitivemachineslibroelectronico
_version_ 1756227860753809409
spelling KOHA-OAI-ECOSUR:547142020-11-25T16:48:43ZCalculus of thought neuromorphic logistic regression in cognitive machines Libro electrónico Rice, Daniel M. autor/a textWaltham, Massachusetts, United States Academic Pressc2014engCalculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus Ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems. The reduced error logistic regression (RELR) method is proposed as such a "Calculus of Thought." This book reviews how RELRs completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELRs new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today's big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior. *Provides a high-level introduction and detailed reviews of the neural, statistical and machine learning knowledge base as a foundation for a new era of smarter machines. *Argues that smarter machine learning to handle both explanation and prediction without cognitive bias must have a foundation in cognitive neuroscience and must embody similar explicit and implicit learning principles that occur in the brain. *Offers a new neuromorphic foundation for machine learning based upon the reduced error logistic regression (RELR) method and provides simple examples of RELR computations in toy problems that can be accessed in spreadsheet workbooks through a companion website.Incluye bibliografía e índice: páginas 271-280Calculus of Thought, 1st Edition.. Preface: A personal perspective.. 1. Calculus ratiocinator.. 2. Most likely inference.. 3. Conditional probability learning.. 4. Causal reasoning.. 5. Neural calculus.. 6. Oscillating neural synchrony.. 7. Neural natural selection and Alzheimer's disease.. 8. Let Us calculate.. Appendix one: The RELR Formulation.. Appendix two: The 2004 Election weekend survey modelCalculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus Ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems. The reduced error logistic regression (RELR) method is proposed as such a "Calculus of Thought." This book reviews how RELRs completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELRs new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today's big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior. *Provides a high-level introduction and detailed reviews of the neural, statistical and machine learning knowledge base as a foundation for a new era of smarter machines. *Argues that smarter machine learning to handle both explanation and prediction without cognitive bias must have a foundation in cognitive neuroscience and must embody similar explicit and implicit learning principles that occur in the brain. *Offers a new neuromorphic foundation for machine learning based upon the reduced error logistic regression (RELR) method and provides simple examples of RELR computations in toy problems that can be accessed in spreadsheet workbooks through a companion website.Adobe Acrobat profesional 6.0 o superiorSubscripción a ELSEVIERComputational neuroscienceCognitive scienceDisponible en líneahttp://www.sciencedirect.com/science/book/9780124104075URN:ISBN:9780124104075Disponible para usuarios de ECOSUR con su clave de acceso