Ensemble

Ensemble Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Ensemble book. This book definitely worth reading, it is an incredibly well-written.

The Ensemble

Aja Gabel
The Ensemble Book PDF

Author : Aja Gabel
Publisher : Penguin
Page : 352 pages
File Size : 41,5 Mb
Release : 2018-05-15
Category : Fiction
ISBN : 9780735214781

Get Book

The Ensemble by Aja Gabel Pdf

"Pitch-perfect." —People "You won’t be able to quit these characters." —goop The addictive novel about four young friends navigating the cutthroat world of classical music and their complex relationships with each other, as ambition, passion, and love intertwine over the course of their lives. Jana. Brit. Daniel. Henry. They would never have been friends if they hadn't needed each other. They would never have found each other except for the art which drew them together. They would never have become family without their love for the music, for each other. Brit is the second violinist, a beautiful and quiet orphan; on the viola is Henry, a prodigy who's always had it easy; the cellist is Daniel, the oldest and an angry skeptic who sleeps around; and on first violin is Jana, their flinty, resilient leader. Together, they are the Van Ness Quartet. After the group's youthful, rocky start, they experience devastating failure and wild success, heartbreak and marriage, triumph and loss, betrayal and enduring loyalty. They are always tied to each other - by career, by the intensity of their art, by the secrets they carry, by choosing each other over and over again. Following these four unforgettable characters, Aja Gabel's debut novel gives a riveting look into the high-stakes, cutthroat world of musicians, and of lives made in concert. The story of Brit and Henry and Daniel and Jana, The Ensemble is a heart-skipping portrait of ambition, friendship, and the tenderness of youth.

Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition)

Lior Rokach
Ensemble Learning Pattern Classification Using Ensemble Methods Second Edition Book PDF

Author : Lior Rokach
Publisher : World Scientific
Page : 301 pages
File Size : 52,9 Mb
Release : 2019-02-27
Category : Computers
ISBN : 9789811201974

Get Book

Ensemble Learning: Pattern Classification Using Ensemble Methods (Second Edition) by Lior Rokach Pdf

This updated compendium provides a methodical introduction with a coherent and unified repository of ensemble methods, theories, trends, challenges, and applications. More than a third of this edition comprised of new materials, highlighting descriptions of the classic methods, and extensions and novel approaches that have recently been introduced.Along with algorithmic descriptions of each method, the settings in which each method is applicable and the consequences and tradeoffs incurred by using the method is succinctly featured. R code for implementation of the algorithm is also emphasized.The unique volume provides researchers, students and practitioners in industry with a comprehensive, concise and convenient resource on ensemble learning methods.

Wind Power Ensemble Forecasting

André Gensler
Wind Power Ensemble Forecasting Book PDF

Author : André Gensler
Publisher : kassel university press GmbH
Page : 216 pages
File Size : 44,7 Mb
Release : 2019-01-16
Category : Weights and measures
ISBN : 9783737606363

Get Book

Wind Power Ensemble Forecasting by André Gensler Pdf

This thesis describes performance measures and ensemble architectures for deterministic and probabilistic forecasts using the application example of wind power forecasting and proposes a novel scheme for the situation-dependent aggregation of forecasting models. For performance measures, error scores for deterministic as well as probabilistic forecasts are compared, and their characteristics are shown in detail. For the evaluation of deterministic forecasts, a categorization by basic error measure and normalization technique is introduced that simplifies the process of choosing an appropriate error measure for certain forecasting tasks. Furthermore, a scheme for the common evaluation of different forms of probabilistic forecasts is proposed. Based on the analysis of the error scores, a novel hierarchical aggregation technique for both deterministic and probabilistic forecasting models is proposed that dynamically weights individual forecasts using multiple weighting factors such as weather situation and lead time dependent weighting. In the experimental evaluation it is shown that the forecasting quality of the proposed technique is able to outperform other state of the art forecasting models and ensembles.

Ensemble Learning Algorithms With Python

Jason Brownlee
Ensemble Learning Algorithms With Python Book PDF

Author : Jason Brownlee
Publisher : Machine Learning Mastery
Page : 450 pages
File Size : 52,9 Mb
Release : 2021-04-26
Category : Computers
ISBN : 8210379456XXX

Get Book

Ensemble Learning Algorithms With Python by Jason Brownlee Pdf

Predictive performance is the most important concern on many classification and regression problems. Ensemble learning algorithms combine the predictions from multiple models and are designed to perform better than any contributing ensemble member. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently and effectively improve predictive modeling performance using ensemble algorithms.

Conducting and Rehearsing the Instrumental Music Ensemble

John F. Colson
Conducting and Rehearsing the Instrumental Music Ensemble Book PDF

Author : John F. Colson
Publisher : Scarecrow Press
Page : 522 pages
File Size : 48,8 Mb
Release : 2012-08-09
Category : Music
ISBN : 9780810882614

Get Book

Conducting and Rehearsing the Instrumental Music Ensemble by John F. Colson Pdf

Conducting and Rehearsing the Instrumental Music Ensemble is the most comprehensive guide on the rehearsal process for conducting instrumental music ensembles. Ideal for the advanced instrumental music conductor seeking to look beyond basic conducting technique, this work breaks the multidimensional activity of working with an ensemble, orchestra, or band into its constituent components. Advanced students of conducting will find within the full range of conducting activities: • Chapters on the infrastructure of the rehearsal, the rehearsal environment, 10 rehearsal essentials, score study, music imagery, inner singing, and rehearsal procedures (with an emphasis on an integrated approach to rehearsing) • The technical priorities of intonation and tuning, rhythm patterns, ensemble sonority (tone, balance, blend, color and texture), and articulation • The musical priorities of tempo and ensemble precision, phrasing and the musical line, style and interpretation, dynamics and musical expression • Emphasizing the expectations of 21st-century conductors, the challenges of conducting and rehearsing contemporary music, preparing conductor profiles and self-evaluations, and moving from the rehearsal process to concert performance Conducting and Rehearsing the Instrumental Music Ensemble is a great resource for teachers and students of conducting, as well as current conductors wishing to further hone their skills.

The Ensemble Practice

P. Palaveev
The Ensemble Practice Book PDF

Author : P. Palaveev
Publisher : John Wiley & Sons
Page : 247 pages
File Size : 41,7 Mb
Release : 2012-10-02
Category : Business & Economics
ISBN : 9781118209547

Get Book

The Ensemble Practice by P. Palaveev Pdf

A detailed road map for wealth managers who want to build an ensemble firm or team and achieve sustained growth, profitability and high valuations Why do ten percent of wealth management firms grow faster than the rest of the industry, often despite the turbulence of the markets? The answer, according to industry consultant and researcher, P. Palaveev, is that the most successful firms are those which, create and promote a team-based service model that serves as the foundation of their enterprise. Find out how and why a team-based service model can play a decisive role in the future growth and sustained success of your wealth management firm Discover the key factors for building a successful ensemble firm and profit from the best practices top team-based firms employ Profit from the author's years of experience working with the world's top wealth management firms and the data he has compiled as a pre-eminent industry researcher Learn about the various organizational structures, partnership models and career path options and how to put them to work building an ensemble practice Get the lowdown on how the savviest traditional broker-dealer firms have formed dynamic ensemble teams within their organizations and learn of the results they've achieved

Accent on Ensembles, Book 1

John O'Reilly,Mark Williams
Accent on Ensembles Book 1 Book PDF

Author : John O'Reilly,Mark Williams
Publisher : Alfred Music
Page : 28 pages
File Size : 53,9 Mb
Release : 2005-05-03
Category : Music
ISBN : 1457415593

Get Book

Accent on Ensembles, Book 1 by John O'Reilly,Mark Williams Pdf

Accent on Ensembles is an exciting book of duets, trios and quartets for flexible instrumentation that correlates with Accent on Achievement, Book 1. Use these ensembles to develop confidence in young players and as a valuable resource for music during contest season. Since the instrumentation is flexible, any combination of instruments can play together. Accent on Ensembles, Book 2 is an exciting book of duets, trios and quartets for flexible instrumentation that correlates with Accent on Achievement, Book 2.

The Wind Ensemble and Its Repertoire

Frank J. Cipolla,Donald Hunsberger
The Wind Ensemble and Its Repertoire Book PDF

Author : Frank J. Cipolla,Donald Hunsberger
Publisher : Alfred Music
Page : 322 pages
File Size : 43,6 Mb
Release : 1999-11-27
Category : Music
ISBN : 1457449943

Get Book

The Wind Ensemble and Its Repertoire by Frank J. Cipolla,Donald Hunsberger Pdf

As part of the mission of The Donald Hunsberger Wind Library, the 1994 hardcover edition (University of Rochester Press) of The Wind Ensemble and Its Repertoire has now been published in a paperback edition. This compendium of research includes "must have" information on the history and execution of the wind ensemble repertoire.

Ensemble Methods

Zhi-Hua Zhou
Ensemble Methods Book PDF

Author : Zhi-Hua Zhou
Publisher : CRC Press
Page : 238 pages
File Size : 45,6 Mb
Release : 2012-06-06
Category : Business & Economics
ISBN : 9781439830031

Get Book

Ensemble Methods by Zhi-Hua Zhou Pdf

An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After presenting background and terminology, the book covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging and voting schemes, the Stacking method, mixture of experts, and diversity measures. It also discusses multiclass extension, noise tolerance, error-ambiguity and bias-variance decompositions, and recent progress in information theoretic diversity. Moving on to more advanced topics, the author explains how to achieve better performance through ensemble pruning and how to generate better clustering results by combining multiple clusterings. In addition, he describes developments of ensemble methods in semi-supervised learning, active learning, cost-sensitive learning, class-imbalance learning, and comprehensibility enhancement.

Outlier Ensembles

Charu C. Aggarwal,Saket Sathe
Outlier Ensembles Book PDF

Author : Charu C. Aggarwal,Saket Sathe
Publisher : Springer
Page : 276 pages
File Size : 54,7 Mb
Release : 2017-04-06
Category : Computers
ISBN : 9783319547657

Get Book

Outlier Ensembles by Charu C. Aggarwal,Saket Sathe Pdf

This book discusses a variety of methods for outlier ensembles and organizes them by the specific principles with which accuracy improvements are achieved. In addition, it covers the techniques with which such methods can be made more effective. A formal classification of these methods is provided, and the circumstances in which they work well are examined. The authors cover how outlier ensembles relate (both theoretically and practically) to the ensemble techniques used commonly for other data mining problems like classification. The similarities and (subtle) differences in the ensemble techniques for the classification and outlier detection problems are explored. These subtle differences do impact the design of ensemble algorithms for the latter problem. This book can be used for courses in data mining and related curricula. Many illustrative examples and exercises are provided in order to facilitate classroom teaching. A familiarity is assumed to the outlier detection problem and also to generic problem of ensemble analysis in classification. This is because many of the ensemble methods discussed in this book are adaptations from their counterparts in the classification domain. Some techniques explained in this book, such as wagging, randomized feature weighting, and geometric subsampling, provide new insights that are not available elsewhere. Also included is an analysis of the performance of various types of base detectors and their relative effectiveness. The book is valuable for researchers and practitioners for leveraging ensemble methods into optimal algorithmic design.

Recent Advances in Ensembles for Feature Selection

Verónica Bolón-Canedo,Amparo Alonso-Betanzos
Recent Advances in Ensembles for Feature Selection Book PDF

Author : Verónica Bolón-Canedo,Amparo Alonso-Betanzos
Publisher : Springer
Page : 205 pages
File Size : 44,7 Mb
Release : 2018-04-30
Category : Technology & Engineering
ISBN : 9783319900803

Get Book

Recent Advances in Ensembles for Feature Selection by Verónica Bolón-Canedo,Amparo Alonso-Betanzos Pdf

This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method. It reviews various techniques for combining partial results, measuring diversity and evaluating ensemble performance. With the advent of Big Data, feature selection (FS) has become more necessary than ever to achieve dimensionality reduction. With so many methods available, it is difficult to choose the most appropriate one for a given setting, thus making the ensemble paradigm an interesting alternative. The authors first focus on the foundations of ensemble learning and classical approaches, before diving into the specific aspects of ensembles for FS, such as combining partial results, measuring diversity and evaluating ensemble performance. Lastly, the book shows examples of successful applications of ensembles for FS and introduces the new challenges that researchers now face. As such, the book offers a valuable guide for all practitioners, researchers and graduate students in the areas of machine learning and data mining.

Ensembles on Configuration Space

Michael J. W. Hall,Marcel Reginatto
Ensembles on Configuration Space Book PDF

Author : Michael J. W. Hall,Marcel Reginatto
Publisher : Springer
Page : 280 pages
File Size : 49,8 Mb
Release : 2016-06-11
Category : Science
ISBN : 9783319341668

Get Book

Ensembles on Configuration Space by Michael J. W. Hall,Marcel Reginatto Pdf

This book describes a promising approach to problems in the foundations of quantum mechanics, including the measurement problem. The dynamics of ensembles on configuration space is shown here to be a valuable tool for unifying the formalisms of classical and quantum mechanics, for deriving and extending the latter in various ways, and for addressing the quantum measurement problem. A description of physical systems by means of ensembles on configuration space can be introduced at a very fundamental level: the basic building blocks are a configuration space, probabilities, and Hamiltonian equations of motion for the probabilities. The formalism can describe both classical and quantum systems, and their thermodynamics, with the main difference being the choice of ensemble Hamiltonian. Furthermore, there is a natural way of introducing ensemble Hamiltonians that describe the evolution of hybrid systems; i.e., interacting systems that have distinct classical and quantum sectors, allowing for consistent descriptions of quantum systems interacting with classical measurement devices and quantum matter fields interacting gravitationally with a classical spacetime.

Leadership Ensemble

Harvey Seifter,Peter Economy
Leadership Ensemble Book PDF

Author : Harvey Seifter,Peter Economy
Publisher : Holt Paperbacks
Page : 240 pages
File Size : 55,5 Mb
Release : 2003-01-06
Category : Business & Economics
ISBN : 0805071865

Get Book

Leadership Ensemble by Harvey Seifter,Peter Economy Pdf

As the only major orchestra without a conductor, Orpheus Chamber Orchestra is a shining example of a highly effective management style based on collaborative leadership. Leadership Ensemble is designed to show business leaders in any industry how to re-create the successful "Orpheus Process" in their own companies by dismantling top-heavy hierarchies; developing flexible, responsive strategies and decision-making procedures; and unleashing employee creativity, responsibility, and productivity. The authors delineate the eight core principles of collaborative management, including shared and rotated leadership, passionate dedication to mission, clarity of roles within an organization, and learning to listen. Spiced with anecdotes and case studies, Leadership Ensemble is an entertaining, practical guide to survival in today's speed-of-light business environment.

Ensemble Methods for Machine Learning

Gautam Kunapuli
Ensemble Methods for Machine Learning Book PDF

Author : Gautam Kunapuli
Publisher : Simon and Schuster
Page : 350 pages
File Size : 47,7 Mb
Release : 2023-05-30
Category : Computers
ISBN : 9781638356707

Get Book

Ensemble Methods for Machine Learning by Gautam Kunapuli Pdf

Ensemble machine learning combines the power of multiple machine learning approaches, working together to deliver models that are highly performant and highly accurate. Inside Ensemble Methods for Machine Learning you will find: Methods for classification, regression, and recommendations Sophisticated off-the-shelf ensemble implementations Random forests, boosting, and gradient boosting Feature engineering and ensemble diversity Interpretability and explainability for ensemble methods Ensemble machine learning trains a diverse group of machine learning models to work together, aggregating their output to deliver richer results than a single model. Now in Ensemble Methods for Machine Learning you’ll discover core ensemble methods that have proven records in both data science competitions and real-world applications. Hands-on case studies show you how each algorithm works in production. By the time you're done, you'll know the benefits, limitations, and practical methods of applying ensemble machine learning to real-world data, and be ready to build more explainable ML systems. About the Technology Automatically compare, contrast, and blend the output from multiple models to squeeze the best results from your data. Ensemble machine learning applies a “wisdom of crowds” method that dodges the inaccuracies and limitations of a single model. By basing responses on multiple perspectives, this innovative approach can deliver robust predictions even without massive datasets. About the Book Ensemble Methods for Machine Learning teaches you practical techniques for applying multiple ML approaches simultaneously. Each chapter contains a unique case study that demonstrates a fully functional ensemble method, with examples including medical diagnosis, sentiment analysis, handwriting classification, and more. There’s no complex math or theory—you’ll learn in a visuals-first manner, with ample code for easy experimentation! What’s Inside Bagging, boosting, and gradient boosting Methods for classification, regression, and retrieval Interpretability and explainability for ensemble methods Feature engineering and ensemble diversity About the Reader For Python programmers with machine learning experience. About the Author Gautam Kunapuli has over 15 years of experience in academia and the machine learning industry. Table of Contents PART 1 - THE BASICS OF ENSEMBLES 1 Ensemble methods: Hype or hallelujah? PART 2 - ESSENTIAL ENSEMBLE METHODS 2 Homogeneous parallel ensembles: Bagging and random forests 3 Heterogeneous parallel ensembles: Combining strong learners 4 Sequential ensembles: Adaptive boosting 5 Sequential ensembles: Gradient boosting 6 Sequential ensembles: Newton boosting PART 3 - ENSEMBLES IN THE WILD: ADAPTING ENSEMBLE METHODS TO YOUR DATA 7 Learning with continuous and count labels 8 Learning with categorical features 9 Explaining your ensembles

Music Assessment for Better Ensembles

Brian P. Shaw
Music Assessment for Better Ensembles Book PDF

Author : Brian P. Shaw
Publisher : Oxford University Press
Page : 200 pages
File Size : 53,8 Mb
Release : 2018-09-07
Category : Music
ISBN : 9780190603175

Get Book

Music Assessment for Better Ensembles by Brian P. Shaw Pdf

Assessment is central to ensemble music. Yet, teachers do not always have the expertise to harness its potential to improve rehearsals and performances, and promote and document student learning. Written specifically for band, choir, and orchestra teachers at all levels, this book contains all of the information necessary to design and use assessment in a thriving music classroom. The first section addresses foundations such as learning targets, metacognition, and growth mindset. Assessment jargon such as formative assessment, summative assessment, Assessment for Learning, self and peer assessment, and authentic assessment is clarified and illustrated with music examples. Readers will learn practical strategies for choosing which concepts to assess, which methods to use, and how to use results to provide accurate and effective feedback to students. The second section brings assessment fundamentals into the music room. Filled with practical advice, each chapter examines a different facet of musicianship. Sample assessments in all performance areas are provided, including music literacy, fundamentals and technique, terminology, interpretation, evaluation and critique, composition and improvisation, beliefs and attitudes, and more. There is an entire chapter devoted to tips for applying assessment and feedback strategies in rehearsals, which can result in a fresh and effective approach to performance preparation. The final section is an examination of grading practices in music classes. Readers will gain information about ensemble grades that communicate what students know and are able to do, rather than whether they remembered their black socks. A variety of approaches, including Standards-Based Grading, are evaluated in light of music teachers' unique situations. The book concludes with ways for music educators to take their first steps toward implementing these strategies in their own teaching, including the use of instructional technology. Assessing like an expert is possible, and this book is just what teachers need to get started.