Assessing And Improving Prediction And Classification
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Assessing And Improving Prediction And Classification
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Author : Timothy Masters
language : en
Publisher: Apress
Release Date : 2017-12-19
Assessing And Improving Prediction And Classification written by Timothy Masters and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Computers categories.
Assess the quality of your prediction and classification models in ways that accurately reflect their real-world performance, and then improve this performance using state-of-the-art algorithms such as committee-based decision making, resampling the dataset, and boosting. This book presents many important techniques for building powerful, robust models and quantifying their expected behavior when put to work in your application. Considerable attention is given to information theory, especially as it relates to discovering and exploiting relationships between variables employed by your models. This presentation of an often confusing subject avoids advanced mathematics, focusing instead on concepts easily understood by those with modest background in mathematics. All algorithms include an intuitive explanation of operation, essential equations, references to more rigorous theory, and commented C++ source code. Many of these techniques are recent developments, still not in widespread use. Others are standard algorithms given a fresh look. In every case, the emphasis is on practical applicability, with all code written in such a way that it can easily be included in any program. What You'll Learn Compute entropy to detect problematic predictors Improve numeric predictions using constrained and unconstrained combinations, variance-weighted interpolation, and kernel-regression smoothing Carry out classification decisions using Borda counts, MinMax and MaxMin rules, union and intersection rules, logistic regression, selection by local accuracy, maximization of the fuzzy integral, and pairwise coupling Harness information-theoretic techniques to rapidly screen large numbers of candidate predictors, identifying those that are especially promising Use Monte-Carlo permutation methods to assess the role of good luck in performance results Compute confidence and tolerance intervals for predictions, as well as confidence levels for classification decisions Who This Book is For Anyone who creates prediction or classification models will find a wealth of useful algorithms in this book. Although all code examples are written in C++, the algorithms are described in sufficient detail that they can easily be programmed in any language.
Assessing And Improving Prediction And Classification
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Author : Timothy Masters
language : en
Publisher: CreateSpace
Release Date : 2013-04-21
Assessing And Improving Prediction And Classification written by Timothy Masters and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-21 with Mathematics categories.
This book begins by presenting methods for performing practical, real-life assessment of the performance of prediction and classification models. It then goes on to discuss techniques for improving the performance of such models by intelligent resampling of training/testing data, combining multiple models into sophisticated committees, and making use of exogenous information to dynamically choose modeling methodologies. Rigorous statistical techniques for computing confidence in predictions and decisions receive extensive treatment. Finally, a hundred pages are devoted to the use of information theory in evaluating and selecting useful predictors. Special attention is paid to Schreiber's Information Transfer, a recent generalization of Grainger Causality. Well commented C++ code is given for every algorithm and technique. The ultimate purpose of this text is three-fold. The first goal is to open the eyes of serious developers to some of the hidden pitfalls that lurk in the model development process. The second is to provide broad exposure for some of the most powerful model enhancement algorithms that have emerged from academia in the last two decades, while not bogging down readers in cryptic mathematical theory. Finally, this text should provide the reader with a toolbox of ready-to-use C++ code that can be easily incorporated into his or her existing programs.
Testing And Tuning Market Trading Systems
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Author : Timothy Masters
language : en
Publisher: Apress
Release Date : 2018-10-26
Testing And Tuning Market Trading Systems written by Timothy Masters and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-26 with Computers categories.
Build, test, and tune financial, insurance or other market trading systems using C++ algorithms and statistics. You’ve had an idea and have done some preliminary experiments, and it looks promising. Where do you go from here? Well, this book discusses and dissects this case study approach. Seemingly good backtest performance isn't enough to justify trading real money. You need to perform rigorous statistical tests of the system's validity. Then, if basic tests confirm the quality of your idea, you need to tune your system, not just for best performance, but also for robust behavior in the face of inevitable market changes. Next, you need to quantify its expected future behavior, assessing how bad its real-life performance might actually be, and whether you can live with that. Finally, you need to find its theoretical performance limits so you know if its actual trades conform to this theoretical expectation, enabling you to dump the system if it does not live up to expectations. This book does not contain any sure-fire, guaranteed-riches trading systems. Those are a dime a dozen... But if you have a trading system, this book will provide you with a set of tools that will help you evaluate the potential value of your system, tweak it to improve its profitability, and monitor its on-going performance to detect deterioration before it fails catastrophically. Any serious market trader would do well to employ the methods described in this book. What You Will Learn See how the 'spaghetti-on-the-wall' approach to trading system development can be done legitimatelyDetect overfitting early in developmentEstimate the probability that your system's backtest results could have been due to just good luckRegularize a predictive model so it automatically selects an optimal subset of indicator candidatesRapidly find the global optimum for any type of parameterized trading systemAssess the ruggedness of your trading system against market changesEnhance the stationarity and information content of your proprietary indicatorsNest one layer of walkforward analysis inside another layer to account for selection bias in complex trading systemsCompute a lower bound on your system's mean future performanceBound expected periodic returns to detect on-going system deterioration before it becomes severeEstimate the probability of catastrophic drawdown Who This Book Is For Experienced C++ programmers, developers, and software engineers. Prior experience with rigorous statistical procedures to evaluate and maximize the quality of systems is recommended as well.
The Statistical Evaluation Of Medical Tests For Classification And Prediction
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Author : Margaret Sullivan Pepe
language : en
Publisher: OUP Oxford
Release Date : 2003-03-13
The Statistical Evaluation Of Medical Tests For Classification And Prediction written by Margaret Sullivan Pepe and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-03-13 with Medical categories.
This book describes statistical techniques for the design and evaluation of research studies on medical diagnostic tests, screening tests, biomarkers and new technologies for classification and prediction in medicine.
Deep Belief Nets In C And Cuda C Volume 1
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Author : Timothy Masters
language : en
Publisher: Apress
Release Date : 2018-04-23
Deep Belief Nets In C And Cuda C Volume 1 written by Timothy Masters and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-23 with Computers categories.
Discover the essential building blocks of the most common forms of deep belief networks. At each step this book provides intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. The first of three in a series on C++ and CUDA C deep learning and belief nets, Deep Belief Nets in C++ and CUDA C: Volume 1 shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a thought process that is capable of learning abstract concepts built from simpler primitives. As such, you’ll see that a typical deep belief net can learn to recognize complex patterns by optimizing millions of parameters, yet this model can still be resistant to overfitting. All the routines and algorithms presented in the book are available in the code download, which also contains some libraries of related routines. What You Will Learn Employ deep learning using C++ and CUDA C Work with supervised feedforward networks Implement restricted Boltzmann machines Use generative samplings Discover why these are important Who This Book Is For Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Understanding Evidence Based Rheumatology
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Author : Hasan Yazici
language : en
Publisher: Springer
Release Date : 2014-10-29
Understanding Evidence Based Rheumatology written by Hasan Yazici and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-29 with Medical categories.
It is imperative that health professionals caring for patients with rheumatic diseases understand how to correctly interpret evidence in their field, taking into account the merits and shortcomings of available data. Understanding Evidence-Based Rheumatology offers a practical assessment of criteria, drugs, trials, and registries and provides useful tools for successfully interpreting this data. The book introduces readers to basic analysis of trial design, statistics and application of data through no-nonsense, easy-to-follow insights. Using numerous examples, chapters outline the difficulties physicians encounter when measuring disease activity in rheumatology and offer strategies for systematically approaching these situations. Ethical issues in study design and reporting are examined and the book closes with a summary of future directions for scientific and clinical studies in rheumatology. Understanding Evidence-Based Rheumatology is an invaluable resource for trainees, clinicians and scientists, preparing them with the necessary tools to correctly gather evidence and shed light on the difficult practice of rheumatology.
Deep Belief Nets In C And Cuda C Volume 3
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Author : Timothy Masters
language : en
Publisher: Apress
Release Date : 2018-07-04
Deep Belief Nets In C And Cuda C Volume 3 written by Timothy Masters and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Computers categories.
Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract concepts built from simpler primitives. These models are especially useful for image processing applications. At each step Deep Belief Nets in C++ and CUDA C: Volume 3 presents intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. Source code for all routines presented in the book, and the executable CONVNET program which implements these algorithms, are available for free download. What You Will Learn Discover convolutional nets and how to use them Build deep feedforward nets using locally connected layers, pooling layers, and softmax outputs Master the various programming algorithms required Carry out multi-threaded gradient computations and memory allocations for this threading Work with CUDA code implementations of all core computations, including layer activations and gradient calculations Make use of the CONVNET program and manual to explore convolutional nets and case studies Who This Book Is For Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Deep Belief Nets In C And Cuda C Volume 2
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Author : Timothy Masters
language : en
Publisher: Apress
Release Date : 2018-05-29
Deep Belief Nets In C And Cuda C Volume 2 written by Timothy Masters and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-29 with Computers categories.
Discover the essential building blocks of a common and powerful form of deep belief net: the autoencoder. You’ll take this topic beyond current usage by extending it to the complex domain for signal and image processing applications. Deep Belief Nets in C++ and CUDA C: Volume 2 also covers several algorithms for preprocessing time series and image data. These algorithms focus on the creation of complex-domain predictors that are suitable for input to a complex-domain autoencoder. Finally, you’ll learn a method for embedding class information in the input layer of a restricted Boltzmann machine. This facilitates generative display of samples from individual classes rather than the entire data distribution. The ability to see the features that the model has learned for each class separately can be invaluable. At each step this book provides you with intuitive motivation, a summary of the most important equations relevant to the topic, and highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. What You'll Learn Code for deep learning, neural networks, and AI using C++ and CUDA C Carry out signal preprocessing using simple transformations, Fourier transforms, Morlet wavelets, and more Use the Fourier Transform for image preprocessing Implement autoencoding via activation in the complex domain Work with algorithms for CUDA gradient computation Use the DEEP operating manual Who This Book Is For Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Handbook On Risk And Need Assessment
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Author : Faye S. Taxman
language : en
Publisher: Taylor & Francis
Release Date : 2016-11-10
Handbook On Risk And Need Assessment written by Faye S. Taxman and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-10 with Social Science categories.
The Handbook on Risk and Need Assessment: Theory and Practice covers risk assessments for individuals being considered for parole or probation. Evidence-based approaches to such decisions help take the emotion and politics out of community corrections. As the United States begins to back away from ineffective, expensive policies of mass incarceration, this handbook will provide the resources needed to help ensure both public safety and the effective rehabilitation of offenders. The ASC Division on Corrections & Sentencing Handbook Series will publish volumes on topics ranging from violence risk assessment to specialty courts for drug users, veterans, or the mentally ill. Each thematic volume focuses on a single topical issue that intersects with corrections and sentencing research.
The Wiley Handbook On What Works With Girls And Women In Conflict With The Law
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Author : Shelley L. Brown
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-14
The Wiley Handbook On What Works With Girls And Women In Conflict With The Law written by Shelley L. Brown and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-14 with Psychology categories.
The Wiley Handbook on What Works with Girls and Women in Conflict with the Law The most practical discussion of the rehabilitation of girls and women in conflict with the law in the correctional arena What Works with Girls and Women in Conflict with the Law is the leading examination of evidence-based practice in the field of gender-responsive corrections. Adopting an international and intersectional approach, the distinguished authors seek to collect the best available data and thinking on what works with girls and women and apply it to the real-world problems facing correctional systems today. As part of its contextual and rich approach to the subject, What Works with girls and women in conflict with the law, covers a broad variety of topics, ranging from theories of female involvement in crime, security classification and risk assessment, evidence-based treatment and supervision approaches, special populations (such as Indigenous women), to legal/policy developments in the field of gender-responsive corrections. Perfect for students and practitioners in the field of psychology, criminology, social work, criminal justice, and corrections, this is the only reference of its kind to focus on the practical applications of the latest theory.
