Activity Learning

The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data. Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, defense, and more. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles, algorithms, and tools to transform vast amounts of raw data efficiently into information and knowledge representation. The first comprehensive look at this new branch of machine learning, this book offers a critical review of the problem of imbalanced learning, covering the state of the art in techniques, principles, and real-world applications. Featuring contributions from experts in both academia and industry, Imbalanced Learning: Foundations, Algorithms, and Applications provides chapter coverage on: Foundations of Imbalanced Learning Imbalanced Datasets: From Sampling to Classifiers Ensemble Methods for Class Imbalance Learning Class Imbalance Learning Methods for Support Vector Machines Class Imbalance and Active Learning Nonstationary Stream Data Learning with Imbalanced Class Distribution Assessment Metrics for Imbalanced Learning Imbalanced Learning: Foundations, Algorithms, and Applications will help scientists and engineers learn how to tackle the problem of learning from imbalanced datasets, and gain insight into current developments in the field as well as future research directions.

Learning is at its best when it is goal-oriented, contextual, interesting, challenging, and interactive. These same winning characteristics also define the best computer games, which suggests that the most effective learning experiences are also engaging. Learning can and should be hard fun! The challenge is to get in touch with what it takes to design learning experiences that will excite your audience. Engaging Learning offers a much-needed guide for training professionals who want to create learning programs that are both effective and engaging. Clark N. Quinn Learning, a system designer, presents a unique framework for systematically aligning the key elements of learning and engagement with a proven design process for e-learning games. This nuts-and-bolts guide, which is both research-based and grounded in experience, offers the tools needed to transform learning experiences from humdrum to fun.

Learning Paths is a down-to-earth practical resource that is filled with illustrative examples, methods, techniques, strategies, processes, and tools for making company-wide, real-time training possible. Created to be flexible, the Learning Path approach can be customized to fit your organization no matter what its type or size. Learning Paths is divided into three sections: The Learning Path Methodology: Walks the reader through the major steps and strategies needed for building Learning Paths. Doing the Right Training: Offers a wide-range of strategies, methods and techniques that can be targeted to the training within a Learning Path and tied to an organization’s particular business needs. Do the Training Right: Shows how to ensure the training within a Learning Path is delivered in the most cost-effective manner and introduces methods for structuring training so that it transfers to the job easily and effectively.

Learn the science of collecting information to make effective decisions Everyday decisions are made without the benefit of accurate information. Optimal Learning develops the needed principles for gathering information to make decisions, especially when collecting information is time-consuming and expensive. Designed for readers with an elementary background in probability and statistics, the book presents effective and practical policies illustrated in a wide range of applications, from energy, homeland security, and transportation to engineering, health, and business. This book covers the fundamental dimensions of a learning problem and presents a simple method for testing and comparing policies for learning. Special attention is given to the knowledge gradient policy and its use with a wide range of belief models, including lookup table and parametric and for online and offline problems. Three sections develop ideas with increasing levels of sophistication: Fundamentals explores fundamental topics, including adaptive learning, ranking and selection, the knowledge gradient, and bandit problems Extensions and Applications features coverage of linear belief models, subset selection models, scalar function optimization, optimal bidding, and stopping problems Advanced Topics explores complex methods including simulation optimization, active learning in mathematical programming, and optimal continuous measurements Each chapter identifies a specific learning problem, presents the related, practical algorithms for implementation, and concludes with numerous exercises. A related website features additional applications and downloadable software, including MATLAB and the Optimal Learning Calculator, a spreadsheet-based package that provides an introduc­tion to learning and a variety of policies for learning.

This is an updated version of a comprehensive a resource for health professionals working with people (primarily adults) who have learning disabilities (intellectual disabilities). It will provide a comprehensive overview of the diverse approaches to treatment and management issues, as well as methods to help them achieve the rehabilitation aims – including the usage of non-healthcare facilities. Split into three sections, the book covers 1: Underlying theory; 2: Assessment; 3: Practical methods of physical treatment and management. Combines history and the theory underlying learning disability and its associated conditions; assessment, and practical physical treatment. Achieves carefully assessed aims through methods appropriate to the individual client. Funding suggestions for working in non-healthcare situations. Features a breadth of content that also appeals to non-physiotherapists.

A new approach to unsupervised learning Evolving technologies have brought about an explosion of information in recent years, but the question of how such information might be effectively harvested, archived, and analyzed remains a monumental challenge—for the processing of such information is often fraught with the need for conceptual interpretation: a relatively simple task for humans, yet an arduous one for computers. Inspired by the relative success of existing popular research on self-organizing neural networks for data clustering and feature extraction, Unsupervised Learning: A Dynamic Approach presents information within the family of generative, self-organizing maps, such as the self-organizing tree map (SOTM) and the more advanced self-organizing hierarchical variance map (SOHVM). It covers a series of pertinent, real-world applications with regard to the processing of multimedia data—from its role in generic image processing techniques, such as the automated modeling and removal of impulse noise in digital images, to problems in digital asset management and its various roles in feature extraction, visual enhancement, segmentation, and analysis of microbiological image data. Self-organization concepts and applications discussed include: Distance metrics for unsupervised clustering Synaptic self-amplification and competition Image retrieval Impulse noise removal Microbiological image analysis Unsupervised Learning: A Dynamic Approach introduces a new family of unsupervised algorithms that have a basis in self-organization, making it an invaluable resource for researchers, engineers, and scientists who want to create systems that effectively model oppressive volumes of data with little or no user intervention.

Learning disability nurses play a leading role in the care and support of people with learning disabilities. Learning Disability Nursing explores the theory and practice of learning disability nursing, with an emphasis on understanding the experiences of learning disability nurses as they seek to practice effectively. It examines key issues faced by people with learning disabilities and those who support them and promotes the role of knowledgeable and reflective practitioners. * Develops a framework for learning disability nursing practice * Examines key issues for people with learning disabilities * Identifies distinctive features of learning disability nursing * Supports learning disability nurses in developing their roles and to support those with learning disabilities in exercising their rights. * Explores ethical and moral dilemmas, challenges and successes

In this updated landmark book, the authors have gathered the seminal work and most current thinking on adult learning into one volume. Learning in Adulthood addresses a wide range of topics including: Who are adult learners? How do adults learn? Why are adults involved in learning activities? How does the social context shape the learning that adults are engaged in? How does aging affect learning ability?

This book advances a design-based approach for the investigation and creation of sustainable organizations. The learning-by-design framework is utilized to examine learning in six successful companies in different industries and national settings and provides a roadmap for improving systematic learning in organizations. Investigates learning-by-design in successful companies. Focuses on the choices organizations make about the design of learning mechanisms. Built around six detailed case studies taken from different industries and national settings. Provides a framework for improving the conditions for systematic and sustainable learning in organizations. Offers a clear process model for action and change.

As more than 90% of spending on the Internet comes from brick and mortar companies it is these operations that will form the client base for e-learning. This book shows those companies how to get e-learning implementation right first time. Don Morisson explores and explains the whole implementation continuum – strategy, vendor selection, technology, implementation, culture change, content development and delivery. Most importantly he stresses that the success or failure of an e-learning initiative is directly related to the underlying strategic thinking. Written for a more mature, second generation e-learning market the book provides a practitioner's handbook to both guide the novice and inform the veteran. * Focuses on the reader's needs * Focuses on the strategic issues of e-learning * Informed by key business drivers * Supported and endorsed by PWC Readership: Senior managers including CEOs, CIOs, CLOs, HR Directors, middle management responsible for implementing and/or delivering e-learning, consultants