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Behavior Analysis With Machine Learning Using R

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Behavior Analysis With Machine Learning Using R

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Author : Enrique Garcia Ceja
language : en
Publisher: CRC Press
Release Date : 2021-11-26

Behavior Analysis With Machine Learning Using R written by Enrique Garcia Ceja and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-26 with Psychology categories.

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records. The included examples demonstrate how to perform common data analysis tasks such as: data exploration, visualization, preprocessing, data representation, model training and evaluation. All of this, using the R programming language and real-life behavioral data. Even though the examples focus on behavior analysis tasks, the covered underlying concepts and methods can be applied in any other domain. No prior knowledge in machine learning is assumed. Basic experience with R and basic knowledge in statistics and high school level mathematics are beneficial. Features: Build supervised machine learning models to predict indoor locations based on WiFi signals, recognize physical activities from smartphone sensors and 3D skeleton data, detect hand gestures from accelerometer signals, and so on. Program your own ensemble learning methods and use Multi-View Stacking to fuse signals from heterogeneous data sources. Use unsupervised learning algorithms to discover criminal behavioral patterns. Build deep learning neural networks with TensorFlow and Keras to classify muscle activity from electromyography signals and Convolutional Neural Networks to detect smiles in images. Evaluate the performance of your models in traditional and multi-user settings. Build anomaly detection models such as Isolation Forests and autoencoders to detect abnormal fish behaviors. This book is intended for undergraduate/graduate students and researchers from ubiquitous computing, behavioral ecology, psychology, e-health, and other disciplines who want to learn the basics of machine learning and deep learning and for the more experienced individuals who want to apply machine learning to analyze behavioral data.

Behavior Analysis With Machine Learning Using R

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Author : Enrique Garcia Ceja
language : en
Publisher: CRC Press
Release Date : 2021-11-25

Behavioral Data Analysis With R And Python

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Author : Florent Buisson
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-06-15

Behavioral Data Analysis With R And Python written by Florent Buisson and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-15 with Business & Economics categories.

Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis. Common data science algorithms and predictive analytics tools treat customer behavioral data, such as clicks on a website or purchases in a supermarket, the same as any other data. Instead, this practical guide introduces powerful methods specifically tailored for behavioral data analysis. Advanced experimental design helps you get the most out of your A/B tests, while causal diagrams allow you to tease out the causes of behaviors even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, thispractical book provides complete examples and exercises in R and Python to help you gain more insight from your data--immediately. Understand the specifics of behavioral data Explore the differences between measurement and prediction Learn how to clean and prepare behavioral data Design and analyze experiments to drive optimal business decisions Use behavioral data to understand and measure cause and effect Segment customers in a transparent and insightful way

Statistical Machine Learning For Human Behaviour Analysis

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Author : Thomas Moeslund
language : en
Publisher: MDPI
Release Date : 2020-06-17

Statistical Machine Learning For Human Behaviour Analysis written by Thomas Moeslund and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-17 with Technology & Engineering categories.

This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.

Machine Learning Predictive Analytics And Optimization In Complex Systems

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Author : John Joseph, Ferdin Joe
language : en
Publisher: IGI Global
Release Date : 2025-06-27

Machine Learning Predictive Analytics And Optimization In Complex Systems written by John Joseph, Ferdin Joe and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-27 with Computers categories.

The integration of machine learning, predictive analytics, and optimization techniques revolutionizes the understanding and management of complex systems. From supply chains and energy grids to healthcare and financial markets, these systems are characterized by dynamic interactions, uncertainty, and large data amounts. Machine learning enables insights into data patterns, analytics predict future behaviors, and optimization methods guide decision-making. When combined, these tools offer solutions for enhancing system performance, resilience, and adaptability. As complexity grows, their collaboration becomes vital for creating intelligent, responsive, and sustainable systems. Machine Learning, Predictive Analytics, and Optimization in Complex Systems examines the integration of intelligent technologies into system design and management, and data analysis. It explores strategies for data-informed decisions, intelligent technology utilization, and security optimization. This book covers topics such as computer engineering, smart ecosystems, and system design, and is a useful resource for computer engineers, data analysts, academicians, researchers, and scientists.

Brain Inspired Machine Learning And Computation For Brain Behavior Analysis

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Author : Rong Chen
language : en
Publisher: Frontiers Media SA
Release Date : 2021-04-16

Brain Inspired Machine Learning And Computation For Brain Behavior Analysis written by Rong Chen and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-16 with Science categories.

Interpretable Machine Learning

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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020

Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.

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 With R

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Author : Brett Lantz
language : en
Publisher: Packt Publishing Ltd
Release Date : 2013-10-25

Machine Learning With R written by Brett Lantz and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-25 with Computers categories.

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.

Hands On Machine Learning With R

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Author : Brad Boehmke
language : en
Publisher: CRC Press
Release Date : 2019-11-07

Hands On Machine Learning With R written by Brad Boehmke and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-07 with Business & Economics categories.

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.

Outstanding User Interfaces With Shiny

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Author : David Granjon
language : en
Publisher: CRC Press
Release Date : 2022-08-31

Outstanding User Interfaces With Shiny written by David Granjon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-31 with Business & Economics categories.

Outstanding User Interfaces with Shiny provides the reader with necessary knowledge to develop beautiful and highly interactive user interfaces. It gives the minimum requirements in HTML/JavaScript and CSS to be able to extend already existing Shiny layouts or develop new templates from scratch. Suitable for anyone with some experience of Shiny, package development and software engineering best practices, this book is an ideal guide for graduates and professionals who wish to bring their app design to the next level. Key Features: Provides a survival kit in web development to seamlessly get started with HTML/CSS/JavaScript Leverage CSS and Sass and higher-level tools like {bslib} to substantially enhance the design of your app in no time A comprehensive guide to the {htmltools} package to seamlessly customize existing layouts Describes in detail how Shiny inputs work and how R and JavaScript communicate Details all the necessary steps to create a production-grade custom template from scratch: packaging, shiny tags creation, validating and testing R components and JavaScript Expose common web development debugging technics Provides a list of existing templates, resources to get started and to explore

Behavior Analysis With Machine Learning Using R

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