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Author: Christoph Molnar Publisher: Lulu.com ISBN: 0244768528 Category : Computers Languages : en Pages : 320
Book Description
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.
Author: Christoph Molnar Publisher: Lulu.com ISBN: 0244768528 Category : Computers Languages : en Pages : 320
Book Description
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.
Author: Norman Foo Publisher: Springer Science & Business Media ISBN: 3540668225 Category : Computers Languages : en Pages : 518
Book Description
This book constitutes the refereed proceedings of the 12th Australian Joint Conference on Artificial Intelligence, AI'99, held in Sydney, Australia in December 1999. The 39 revised full papers presented together with 15 posters were carefully reviewed and selected from more than 120 submissions. The book is divided in topical sections on machine learning, neural nets, knowledge representation, natural language processing, belief revision, adaptive algorithms, automated reasonning, neural learning, heuristics, and applications
Author: Earl Cox Publisher: Elsevier ISBN: 0080470599 Category : Computers Languages : en Pages : 553
Book Description
Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As you'll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems. You don't need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system. - Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement more effective data mining systems - Helps you to understand the trade-offs implicit in various models and model architectures - Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction - Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model - In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem - Presents examples in C, C++, Java, and easy-to-understand pseudo-code - Extensive online component, including sample code and a complete data mining workbench
Author: Rohit Raja Publisher: John Wiley & Sons ISBN: 1119791782 Category : Computers Languages : en Pages : 500
Book Description
DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.
Author: Gisele L. Pappa Publisher: Springer Science & Business Media ISBN: 3642025412 Category : Computers Languages : en Pages : 198
Book Description
Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from data. We focus on genetic programming in this book because it is the paradigmatic type of machine learning method for automating the generation of programs and because it has the advantage of performing a global search in the space of candidate solutions (data mining algorithms in our case), but in principle other types of search methods for this task could be investigated in the future.
Author: Jacek Koronacki Publisher: Springer Science & Business Media ISBN: 3642051766 Category : Computers Languages : en Pages : 521
Book Description
Professor Richard S. Michalski passed away on September 20, 2007. Once we learned about his untimely death we immediately realized that we would no longer have with us a truly exceptional scholar and researcher who for several decades had been inf- encing the work of numerous scientists all over the world - not only in his area of expertise, notably machine learning, but also in the broadly understood areas of data analysis, data mining, knowledge discovery and many others. In fact, his influence was even much broader due to his creative vision, integrity, scientific excellence and exceptionally wide intellectual horizons which extended to history, political science and arts. Professor Michalski’s death was a particularly deep loss to the whole Polish sci- tific community and the Polish Academy of Sciences in particular. After graduation, he began his research career at the Institute of Automatic Control, Polish Academy of Science in Warsaw. In 1970 he left his native country and hold various prestigious positions at top US universities. His research gained impetus and he soon established himself as a world authority in his areas of interest – notably, he was widely cons- ered a father of machine learning.
Author: J. Ross Quinlan Publisher: Morgan Kaufmann ISBN: 9781558602380 Category : Computers Languages : en Pages : 286
Book Description
This book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use, the source code (about 8,800 lines), and implementation notes.
Author: Jano van Hemert Publisher: Springer ISBN: 354078604X Category : Computers Languages : en Pages : 300
Book Description
Coverage in this proceedings volume presents the latest research and details current developments and applications in metaheuristics, a paradigm to effectively solve difficult combinatorial optimization problems in industry, economics, and science.
Author: Mahdi H. Miraz Publisher: Springer ISBN: 3030239438 Category : Computers Languages : en Pages : 323
Book Description
This book constitutes the refereed conference proceedings of the Second International Conference on Emerging Technologies in Computing, iCEtiC 2019, held in London, UK, in August 2019. The 24 revised full papers were reviewed and selected from 52 submissions and are organized in topical sections covering blockchain and cloud computing, security, wireless sensor networks and Internet of Things, (IoT), FinTech, AI, big data and data analytics.
Author: P. Cheeseman Publisher: Springer Science & Business Media ISBN: 1461226600 Category : Mathematics Languages : en Pages : 475
Book Description
This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.
Author: Christoph Molnar
Author: Christoph Molnar
Author: Norman Foo
Author: Earl Cox
Author: Rohit Raja
Author: Gisele L. Pappa
Author: Jacek Koronacki
Author: J. Ross Quinlan
Author: Jano van Hemert
Author: Mahdi H. Miraz
Author: P. Cheeseman