MACHINE LEARNING. TÉCNICAS DE APRENDIZAJE SUPERVISADO A TRAVÉS DE R PDF Download
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Author: Cesar Perez Lopez
Publisher: CESAR PEREZ
ISBN: 1716967090
Category : Computers
Languages : en
Pages : 205
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Book Description
En este libro se desarrollarán técnicas de aprendizaje supervisado relativas a regresión. Más concretamente, se profundizará en los modelos lineales de regresión múltiple con toda su problemática de identificación, estimación y diagnosis. Se hace especial hincapié en el tratamiento de la multicolinealidad a través de la Ridge Regression (regresión en cadena) y el método PLS de los mínimos cuadrados parciales. Se dedica una parcela importante del contenido a los modelos de variable dependiente limitada y recuento, con especial mención a los modelos Logit y Probit. Por último se tratan también los modelos predictivos del análisis de la varianza y la covarianza.
Author: Cesar Perez Lopez
Publisher: CESAR PEREZ
ISBN: 1716967090
Category : Computers
Languages : en
Pages : 205
Get Book Here
Book Description
En este libro se desarrollarán técnicas de aprendizaje supervisado relativas a regresión. Más concretamente, se profundizará en los modelos lineales de regresión múltiple con toda su problemática de identificación, estimación y diagnosis. Se hace especial hincapié en el tratamiento de la multicolinealidad a través de la Ridge Regression (regresión en cadena) y el método PLS de los mínimos cuadrados parciales. Se dedica una parcela importante del contenido a los modelos de variable dependiente limitada y recuento, con especial mención a los modelos Logit y Probit. Por último se tratan también los modelos predictivos del análisis de la varianza y la covarianza.
Author: Lorna Uden
Publisher:
ISBN: 9783030207991
Category : Artificial intelligence
Languages : en
Pages : 488
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Book Description
This book constitutes the refereed proceedings of the 8th International Workshop on Learning Technology for Education Challenges, LTEC 2019, held in Zamora, Spain, in July 2019. The 41 revised full papers presented were carefully reviewed and selected from 83 submissions. The papers are organized in the following topical sections: learning technolgies; learning tools and environment; e-learning and MOOCs; learning practices; social media learning tools; machine learning and evaluation support programs. LTEC 2019 examines how these technologies and pedagogical advances can be used to change the way teachers teach and students learn, while giving special emphasis to the pedagogically effective ways we can harness these new technologies in education.
Author: Carlos Brito-Loeza
Publisher: Springer Nature
ISBN: 3030433641
Category : Computers
Languages : en
Pages : 161
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Book Description
This book constitutes the proceedings of the Third International Symposium on Intelligent Computing Systems, ISICS 2020, held in Sharjah, United Arab Emirates, in March 2020. The 13 full papers presented in this volume were carefully reviewed and selected from 46 submissions. They deal with the field of intelligent computing systems focusing on artificial intelligence, computer vision and image processing.
Author: Andreas S. Weigend
Publisher: Routledge
ISBN: 042997227X
Category : Social Science
Languages : en
Pages : 665
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Book Description
The book is a summary of a time series forecasting competition that was held a number of years ago. It aims to provide a snapshot of the range of new techniques that are used to study time series, both as a reference for experts and as a guide for novices.
Author: Johs. Hjellbrekke
Publisher: Routledge
ISBN: 1315516241
Category : Social Science
Languages : en
Pages : 118
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Book Description
Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930–2002). This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis. The book is written as a non-technical introduction, intended for the advanced undergraduate level and onwards. MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. In seven chapters, this non-technical book will provide the reader with a comprehensive introduction and the needed knowledge to do analyses on his/her own: CA, MCA, specific MCA, the integration of MCA and variance analysis, of MCA and ascending hierarchical cluster analysis and class-specific MCA on subgroups. Special attention will be given to the construction of social spaces, to the construction of typologies and to group internal oppositions. This is a book on data analysis for the social sciences rather than a book on statistics. The main emphasis is on how to apply MCA to the analysis of practical research questions. It does not require a solid understanding of statistics and/or mathematics, and provides the reader with the needed knowledge to do analyses on his/her own.
Author: Rafael Valencia-García
Publisher: Springer
ISBN: 3319672835
Category : Computers
Languages : en
Pages : 341
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Book Description
This book constitutes the proceedings of the Third International Conference on Technologies and Innovation, CITI 2017, held in Guayaquil, Ecuador, in October 2017. The 24 papers presented in this volume were carefully reviewed and selected from 68 submissions. They were organized in topical sections named: cloud and mobile computing; knowledge based and expert systems; applications in healthcare and wellness; e-learning; and ICT in agronomy.
Author: Ethem Alpaydin
Publisher: MIT Press
ISBN: 0262529513
Category : Computers
Languages : en
Pages : 225
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Book Description
A concise overview of machine learning—computer programs that learn from data—which underlies applications that include recommendation systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don't yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as “Big Data” has gotten bigger, the theory of machine learning—the foundation of efforts to process that data into knowledge—has also advanced. In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications. Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context. He describes the basics of machine learning and some applications; the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances, with such applications as customer segmentation and learning recommendations; and reinforcement learning, when an autonomous agent learns act so as to maximize reward and minimize penalty. Alpaydin then considers some future directions for machine learning and the new field of “data science,” and discusses the ethical and legal implications for data privacy and security.
Author: Frédéric Magoules
Publisher: John Wiley & Sons
ISBN: 1848214227
Category : Computers
Languages : en
Pages : 186
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Book Description
The energy consumption of a building has, in recent years, become a determining factor during its design and construction. With carbon footprints being a growing issue, it is important that buildings be optimized for energy conservation and CO2 reduction. This book therefore presents AI models and optimization techniques related to this application. The authors start with a review of recent models for the prediction of building energy consumption: engineering methods, statistical methods, artificial intelligence methods, ANNs and SVMs in particular. The book then focuses on SVMs, by first applying them to building energy consumption, then presenting the principles and various extensions, and SVR. The authors then move on to RDP, which they use to determine building energy faults through simulation experiments before presenting SVR model reduction methods and the benefits of parallel computing. The book then closes by presenting some of the current research and advancements in the field.
Author: Maykel Verkuyten
Publisher: Routledge
ISBN: 1135075530
Category : Psychology
Languages : en
Pages : 289
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Book Description
Identity and Cultural Diversity examines immigration and its effect on diversity from a social psychological perspective. Immigration increases cultural diversity and raises difficult questions of belonging, adaptation, and the unity of societies: questions of identity may be felt by people struggling with the basic problem of who they are and where they fit in, and although cultural diversity can enrich communities and societies it also sometimes leads to a new tribalism, which threatens democracy and social cohesion. The author Maykel Verkuyten considers how people give meaning to the fact that they belong to ethnic, racial, religious and national groups, and the implications this can have for social cohesion. The opening chapters consider the nature of social identity and group identification, and include discussions of identity development in adolescence, acculturation, and multiple and dual identities. Verkuyten then considers one of the most pernicious social problems: how conflict emerges from perceiving others as different. He examines when and why group distinctions grow into conflicts and considers the role of cultural diversity beliefs, such as multiculturalism and assimilation. The book concludes by exploring productive ways of managing cultural diversity. Written in an engaging style, Identity and Cultural Diversity will be essential reading for undergraduate and postgraduate students of social and cultural psychology and other social sciences, and it also makes key themes in social psychology accessible to a wider audience outside academia.
Author: Chi Hau Chen
Publisher: World Scientific
ISBN: 9814460958
Category : Computers
Languages : en
Pages : 410
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Book Description
The major progress in computer vision allows us to make extensive use of medical imaging data to provide us better diagnosis, treatment and predication of diseases. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information from image sequence and provide 3D and 4D information that helps with better human understanding. Many powerful tools have been available through image segmentation, machine learning, pattern classification, tracking, reconstruction to bring much needed quantitative information not easily available by trained human specialists. The aim of the book is for both medical imaging professionals to acquire and interpret the data, and computer vision professionals to provide enhanced medical information by using computer vision techniques. The final objective is to benefit the patients without adding to the already high medical costs.
