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Book Active Evaluation of Predictive Models

Download or read book Active Evaluation of Predictive Models written by Christoph Sawade and published by Universitätsverlag Potsdam. This book was released on 2013 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book On the Development and Evaluation of Predictive Models

Download or read book On the Development and Evaluation of Predictive Models written by Ning Xu and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Explanatory Model Analysis

Download or read book Explanatory Model Analysis written by Przemyslaw Biecek and published by CRC Press. This book was released on 2021-02-15 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model's performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems.

Book Predictive Models for Decision Support in the COVID 19 Crisis

Download or read book Predictive Models for Decision Support in the COVID 19 Crisis written by Joao Alexandre Lobo Marques and published by Springer Nature. This book was released on 2020-11-30 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.

Book Applied Predictive Modeling

    Book Details:
  • Author : Max Kuhn
  • Publisher : Springer Science & Business Media
  • Release : 2013-05-17
  • ISBN : 1461468493
  • Pages : 595 pages

Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

Book Applied Predictive Modeling

Download or read book Applied Predictive Modeling written by Steven Taylor and published by Steven Taylor. This book was released on 2020-07-14 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling Predictive modeling uses statistics in order to predict outcomes. However, predictive modeling can be applied to future and to any other kind of unknown event, regardless of when it happened. When it comes to the applications of predictive modeling, techniques are used in various fields including algorithmic trading, uplift modeling, archaeology, health care, customer relationship management and many others. This book covers the predictive modeling process with fundamental steps of the process, data preprocessing, data splitting and crucial steps of model tuning and improving model performance. Further, the book will introduce you to the most common classification and regression techniques including logistic regression which is widely used when it comes to the finding the probability of event success or event failure. You will get to know the common predictive modeling techniques as well such as stepwise regression, polynomial regression and ridge regression which will help you when you are dealing with the data that suffers from very common multicollinearity where independent variables are highly correlated. The text then provides fundamental steps to effective predictive modeling. In the second chapter, you will learn how to build your own predictive model with logistic regression and Python. You will find data sets as well as corresponding codes. On of the crucial predictive modeling steps is model tuning, so you will learn some common techniques used in order to improve your model performance. You will get to know how to tune the parameters commonly used to increase the overall predictive power. Predictive modeling comes with a few obstacles and challenges like class imbalance. Imbalanced classes commonly put the accuracy of the model out of business, but you will learn how to properly handle class imbalance which will significantly improve the accuracy of your model. The book is multi-purpose focused on to predictive modeling process and predictive modeling techniques, so it will be of great help for those who are interested in predictive modeling techniques and applications. So, it is the right time to simplify the analysis, boost productivity as well as save time. The book will be your companion on your journey towards highly accurate predictive models. What you will learn in Applied Predictive Modeling: Most common predictive modeling techniques Types of regression models The overall predictive modeling process Fundamental steps to effective and highly accurate predictive modeling How to build predictive model with logistic regression with code listings How to build predictive model using Python How to enhance your model performance Parameters for increasing the overall predictive power How to handle class imbalance Common causes of poor model performance Get this book now and learn more about Applied Predictive Modeling!

Book Evaluating Predictive Models

Download or read book Evaluating Predictive Models written by and published by . This book was released on 2017 with total page 2 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Feature Engineering and Selection

Download or read book Feature Engineering and Selection written by Max Kuhn and published by CRC Press. This book was released on 2019-07-25 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Book Predictive Modeling and Analytics

Download or read book Predictive Modeling and Analytics written by Jeffrey Strickland and published by Lulu.com. This book was released on 2014-08-06 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about predictive modeling. Yet, each chapter could easily be handled by an entire volume of its own. So one might think of this as a survey of predictive models, both statistical and machine learning. We define A predictive model as a statistical model or machine learning model used to predict future behavior based on past behavior. In order to use this book, the reader should have a basic understanding of statistics (statistical inference, models, tests, etc.)-this is an advanced book. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. The book is organized so that statistical models are presented first (hopefully in a logical order), followed by machine learning models, and then applications: uplift modeling and time series. One could use this as a textbook with problem solving in R (there are no "by-hand" exercises).

Book Enhancing the Efficacy of Predictive Analytical Modeling in Operational Management Decision Making

Download or read book Enhancing the Efficacy of Predictive Analytical Modeling in Operational Management Decision Making written by Hossein Najmizadehbaghini and published by . This book was released on 2019 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, we focus on enhancing the efficacy of predictive modeling in operational management decision making in two different settings: Essay 1 focuses on demand forecasting for the companies and the second study utilizes longitudinal data to analyze the illicit drug seizure and overdose deaths in the United States. In Essay 1, we utilize an operational system (newsvendor model) to evaluate the forecast method outcome and provide guidelines for forecast method (the exponential smoothing model) performance assessment and judgmental adjustments. To assess the forecast outcome, we consider not only the common forecast error minimization approach but also the profit maximization at the end of the forecast horizon. Including profit in our assessment enables us to determine if error minimization always results in maximum profit. We also look at the different levels of profit margin to analyze their impact on the forecasting method performance. Our study also investigates how different demand patterns influence maximizing the forecasting method performance. Our study shows that the exponential smoothing model family has a better performance in high-profit products, and the rate of decrease in performance versus demand uncertainty is higher in a stationary demand environment.In the second essay, we focus on illicit drug overdose death rate. Illicit drug overdose deaths are the leading cause of injury death in the United States. In 2017, overdose death reached the highest ever recorded level (70,237), and statistics show that it is a growing problem. The age adjusted rate of drug overdose deaths in 2017 (21.7 per 100,000) is 9.6% higher than the rate in 2016 (19.8 per 100,000) (U. S. Drug Enforcement Administration, 2018, p. V). Also, Marijuana consumption among youth has increased since 2009. The magnitude of the illegal drug trade and its resulting problems have led the government to produce large and comprehensive datasets on a variety of phenomena relating to illicit drugs. In this study, we utilize these datasets to examine how marijuana usage among youth influence excessive drug usage. We measure excessive drug usage in terms of drug overdose death rate per state. Our study shows that illegal marijuana consumption increases excessive drug use. Also, we analyze the pattern of most frequently seized illicit drugs and compare it with drugs that are most frequently involved in a drug overdose death. We further our analysis to study seizure patterns across layers of heroin and cocaine supply chain across states. This analysis reveals that most active layers of the heroin supply chain in the American market are retailers and wholesalers, while multi-kilo traffickers are the most active players in the cocaine supply chain. In summary, the studies in this dissertation explore the use of analytical, descriptive, and predictive models to detect patterns to improve efficacy and initiate better operational management decision making.

Book Open file Report

Download or read book Open file Report written by and published by . This book was released on 1986 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Predictive Modelling for Energy Management and Power Systems Engineering

Download or read book Predictive Modelling for Energy Management and Power Systems Engineering written by Ravinesh Deo and published by Elsevier. This book was released on 2020-09-30 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets. Presents advanced optimization techniques to improve existing energy demand system Provides data-analytic models and their practical relevance in proven case studies Explores novel developments in machine-learning and artificial intelligence applied in energy management Provides modeling theory in an easy-to-read format

Book Future of AI in Biomedicine and Biotechnology

Download or read book Future of AI in Biomedicine and Biotechnology written by Khade, Shankar Mukundrao and published by IGI Global. This book was released on 2024-05-30 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: The healthcare industry is grappling with numerous challenges, including rising costs, inefficiencies in service delivery, and the need for personalized treatment approaches. Traditional healthcare management and delivery methods must be improved in addressing these issues, leading to a growing demand for innovative solutions. Additionally, the exponential growth of medical data and the complexity of biomedical research and biotechnology presents a daunting challenge in harnessing this data effectively for improved patient care and medical advancements. There is a pressing need for a comprehensive understanding of how artificial intelligence (AI) can be leveraged to tackle these challenges and drive meaningful change in the healthcare sector. Future of AI in Biomedicine and Biotechnology offers a timely and insightful solution to the challenges faced by the healthcare industry. This book is not just a theoretical exploration; it is a practical roadmap for healthcare professionals, researchers, policymakers, and entrepreneurs seeking to navigate the complexities of AI in healthcare. By exploring the intersection of AI with biomedical sciences and biotechnology, this book provides a comprehensive guide to harnessing the power of AI for transformative healthcare innovation.

Book Brain Function Assessment in Learning

Download or read book Brain Function Assessment in Learning written by Claude Frasson and published by Springer. This book was released on 2017-09-11 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the First International Conference on Brain Function Assessment in Learning, BFAL 2017, held in Patras, Greece, in September 2017. The 16 revised full papers presented together with 2 invited talks and 6 posters were carefully selected from 28 submissions. The BFAL conference aims to regroup research in multidisciplinary domains such as neuroscience, health, computer science, artificial intelligence, human-computer interaction, education and social interaction on the theme of Brain Function Assessment in Learning.

Book QSAR in Safety Evaluation and Risk Assessment

Download or read book QSAR in Safety Evaluation and Risk Assessment written by Huixiao Hong and published by Elsevier. This book was released on 2023-08-12 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: QSAR in Safety Evaluation and Risk Assessment provides comprehensive coverage on QSAR methods, tools, data sources, and models focusing on applications in products safety evaluation and chemicals risk assessment. Organized into five parts, the book covers almost all aspects of QSAR modeling and application. Topics in the book include methods of QSAR, from both scientific and regulatory viewpoints; data sources available for facilitating QSAR models development; software tools for QSAR development; and QSAR models developed for assisting safety evaluation and risk assessment. Chapter contributors are authored by a lineup of active scientists in this field. The chapters not only provide professional level technical summarizations but also cover introductory descriptions for all aspects of QSAR for safety evaluation and risk assessment. Provides comprehensive content about the QSAR techniques and models in facilitating the safety evaluation of drugs and consumer products and risk assesment of environmental chemicals Includes some of the most cutting-edge methodologies such as deep learning and machine learning for QSAR Offers detailed procedures of modeling and provides examples of each model's application in real practice

Book Assessment of the Performance of Engineered Waste Containment Barriers

Download or read book Assessment of the Performance of Engineered Waste Containment Barriers written by National Research Council and published by National Academies Press. This book was released on 2007-08-22 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: President Carter's 1980 declaration of a state of emergency at Love Canal, New York, recognized that residents' health had been affected by nearby chemical waste sites. The Resource Conservation and Recovery Act, enacted in 1976, ushered in a new era of waste management disposal designed to protect the public from harm. It required that modern waste containment systems use "engineered" barriers designed to isolate hazardous and toxic wastes and prevent them from seeping into the environment. These containment systems are now employed at thousands of waste sites around the United States, and their effectiveness must be continually monitored. Assessment of the Performance of Engineered Waste Containment Barriers assesses the performance of waste containment barriers to date. Existing data suggest that waste containment systems with liners and covers, when constructed and maintained in accordance with current regulations, are performing well thus far. However, they have not been in existence long enough to assess long-term (postclosure) performance, which may extend for hundreds of years. The book makes recommendations on how to improve future assessments and increase confidence in predictions of barrier system performance which will be of interest to policy makers, environmental interest groups, industrial waste producers, and industrial waste management industry.