Decision Forests

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Publisher : Foundations and Trends(r) in C
ISBN 13 : 9781601985408
Total Pages : 162 pages
Book Rating : 4.9/5 (854 download)

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Book Synopsis Decision Forests by : Antonio Criminisi

Download or read book Decision Forests written by Antonio Criminisi and published by Foundations and Trends(r) in C. This book was released on 2012-03 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a unified, efficient model of random decision forests which can be used in a number of applications such as scene recognition from photographs, object recognition in images, automatic diagnosis from radiological scans and document analysis.

Decision Estimation and Classification

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Publisher :
ISBN 13 :
Total Pages : 280 pages
Book Rating : 4.3/5 (97 download)

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Book Synopsis Decision Estimation and Classification by : Charles W. Therrien

Download or read book Decision Estimation and Classification written by Charles W. Therrien and published by . This book was released on 1989-01-17 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Very Good,No Highlights or Markup,all pages are intact.

Interpretable Machine Learning

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Publisher : Lulu.com
ISBN 13 : 0244768528
Total Pages : 320 pages
Book Rating : 4.2/5 (447 download)

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Book Synopsis Interpretable Machine Learning by : Christoph Molnar

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Machine Learning and Knowledge Discovery in Databases

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Publisher : Springer Science & Business Media
ISBN 13 : 354087478X
Total Pages : 714 pages
Book Rating : 4.5/5 (48 download)

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Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Walter Daelemans

Download or read book Machine Learning and Knowledge Discovery in Databases written by Walter Daelemans and published by Springer Science & Business Media. This book was released on 2008-09-04 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.

Pattern Recognition

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Publisher : Elsevier
ISBN 13 : 008051362X
Total Pages : 705 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Pattern Recognition by : Sergios Theodoridis

Download or read book Pattern Recognition written by Sergios Theodoridis and published by Elsevier. This book was released on 2003-05-15 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms.*Approaches pattern recognition from the designer's point of view*New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere*Supplemented by computer examples selected from applications of interest

Technometrics

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Publisher :
ISBN 13 :
Total Pages : 512 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Technometrics by :

Download or read book Technometrics written by and published by . This book was released on 1990 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning and Data Science Blueprints for Finance

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492073008
Total Pages : 426 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Machine Learning and Data Science Blueprints for Finance by : Hariom Tatsat

Download or read book Machine Learning and Data Science Blueprints for Finance written by Hariom Tatsat and published by "O'Reilly Media, Inc.". This book was released on 2020-10-01 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You'll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

Classification and Regression Trees

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Publisher : Routledge
ISBN 13 : 135146048X
Total Pages : 370 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Classification and Regression Trees by : Leo Breiman

Download or read book Classification and Regression Trees written by Leo Breiman and published by Routledge. This book was released on 2017-10-19 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

Image Processing and Pattern Recognition

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Publisher : Elsevier
ISBN 13 : 0080551440
Total Pages : 407 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Image Processing and Pattern Recognition by : Cornelius T. Leondes

Download or read book Image Processing and Pattern Recognition written by Cornelius T. Leondes and published by Elsevier. This book was released on 1998-02-09 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image Processing and Pattern Recognition covers major applications in the field, including optical character recognition, speech classification, medical imaging, paper currency recognition, classification reliability techniques, and sensor technology. The text emphasizes algorithms and architectures for achieving practical and effective systems, and presents many examples. Practitioners, researchers, and students in computer science, electrical engineering, andradiology, as well as those working at financial institutions, will value this unique and authoritative reference to diverse applications methodologies.Coverage includes: - Optical character recognition - Speech classification - Medical imaging - Paper currency recognition - Classification reliability techniques - Sensor technology Algorithms and architectures for achieving practical and effective systems are emphasized, with many examples illustrating the text. Practitioners, researchers, and students in computer science, electrical engineering, and radiology, as wellk as those working at financial institutions, will find this volume a unique and comprehensive reference source for this diverse applications area.

Pattern Classification

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Publisher : John Wiley & Sons
ISBN 13 : 111858600X
Total Pages : 680 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Pattern Classification by : Richard O. Duda

Download or read book Pattern Classification written by Richard O. Duda and published by John Wiley & Sons. This book was released on 2012-11-09 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first edition, published in 1973, has become a classicreference in the field. Now with the second edition, readers willfind information on key new topics such as neural networks andstatistical pattern recognition, the theory of machine learning,and the theory of invariances. Also included are worked examples,comparisons between different methods, extensive graphics, expandedexercises and computer project topics. An Instructor's Manual presenting detailed solutions to all theproblems in the book is available from the Wiley editorialdepartment.

Nonlinear Estimation and Classification

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Publisher : Springer Science & Business Media
ISBN 13 : 0387215794
Total Pages : 465 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Nonlinear Estimation and Classification by : David D. Denison

Download or read book Nonlinear Estimation and Classification written by David D. Denison and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data. This is due in part to recent advances in data collection and computing technologies. As a result, fundamental statistical research is being undertaken in a variety of different fields. Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing. The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics. The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future.

Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques

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Publisher : IGI Global
ISBN 13 : 1605663379
Total Pages : 325 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques by : Marwala, Tshilidzi

Download or read book Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques written by Marwala, Tshilidzi and published by IGI Global. This book was released on 2009-04-30 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is for those who use data analysis to build decision support systems, particularly engineers, scientists and statisticians"--Provided by publisher.

Spotlight on Modern Transformer Design

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Publisher : Springer Science & Business Media
ISBN 13 : 1848826672
Total Pages : 427 pages
Book Rating : 4.8/5 (488 download)

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Book Synopsis Spotlight on Modern Transformer Design by : Pavlos Stylianos Georgilakis

Download or read book Spotlight on Modern Transformer Design written by Pavlos Stylianos Georgilakis and published by Springer Science & Business Media. This book was released on 2009-07-30 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spotlight on Modern Transformer Design introduces a novel approach to transformer design using artificial intelligence (AI) techniques in combination with finite element method (FEM). Today, AI is widely used for modeling nonlinear and large-scale systems, especially when explicit mathematical models are difficult to obtain or completely lacking. Moreover, AI is computationally efficient in solving hard optimization problems. Many numerical examples throughout the book illustrate the application of the techniques discussed to a variety of real-life transformer design problems, including: • problems relating to the prediction of no-load losses; • winding material selection; • transformer design optimisation; • and transformer selection. Spotlight on Modern Transformer Design is a valuable learning tool for advanced undergraduate and graduate students, as well as researchers and power engineering professionals working in electric utilities and industries, public authorities, and design offices.

Decision Forests for Computer Vision and Medical Image Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 1447149297
Total Pages : 367 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Decision Forests for Computer Vision and Medical Image Analysis by : Antonio Criminisi

Download or read book Decision Forests for Computer Vision and Medical Image Analysis written by Antonio Criminisi and published by Springer Science & Business Media. This book was released on 2013-01-30 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.

Pattern Recognition

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Publisher : World Scientific
ISBN 13 : 9810246846
Total Pages : 635 pages
Book Rating : 4.8/5 (12 download)

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Book Synopsis Pattern Recognition by : Sankar K. Pal

Download or read book Pattern Recognition written by Sankar K. Pal and published by World Scientific. This book was released on 2001 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource.

Data Mining With Decision Trees: Theory And Applications (2nd Edition)

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Publisher : World Scientific
ISBN 13 : 9814590096
Total Pages : 328 pages
Book Rating : 4.8/5 (145 download)

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Book Synopsis Data Mining With Decision Trees: Theory And Applications (2nd Edition) by : Oded Z Maimon

Download or read book Data Mining With Decision Trees: Theory And Applications (2nd Edition) written by Oded Z Maimon and published by World Scientific. This book was released on 2014-09-03 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced.This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition.This book invites readers to explore the many benefits in data mining that decision trees offer:

Statistical Decision Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 0387731946
Total Pages : 696 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Statistical Decision Theory by : F. Liese

Download or read book Statistical Decision Theory written by F. Liese and published by Springer Science & Business Media. This book was released on 2008-12-30 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: For advanced graduate students, this book is a one-stop shop that presents the main ideas of decision theory in an organized, balanced, and mathematically rigorous manner, while observing statistical relevance. All of the major topics are introduced at an elementary level, then developed incrementally to higher levels. The book is self-contained as it provides full proofs, worked-out examples, and problems. The authors present a rigorous account of the concepts and a broad treatment of the major results of classical finite sample size decision theory and modern asymptotic decision theory. With its broad coverage of decision theory, this book fills the gap between standard graduate texts in mathematical statistics and advanced monographs on modern asymptotic theory.