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Interpretability of Computational Intelligence Based Regression Models

, and interpretability of the resulting rule-based systems can be ensured by special model reduction and visualization techniques. The first;

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Hybrid Strategies for Improving Bayesian Networks

as performance, as well as interpretability and use of its results; incorporating models of multiple regression for structure learning, and;

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Artificial Intelligence for Automated Pricing Based on Product Descriptions

and deep learning methods for pricing, including from regression methods to hybrid and ensemble methods. The computational experiments are;

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Pattern Recognition and Computational Intelligence Techniques Using Matlab

This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way;

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Data Science and Big Data: An Environment of Computational Intelligence

data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies;

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Decision Support for Product Development

This book describes how to use computational intelligence and artificial intelligence tools to improve the decision-making process in new;

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Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications

machine learning, summarization, interpretability and XAI. Moreover, several application-based papers are included, e.g. on image processing;

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Interpreting Machine Learning Models

based methods, saliency maps methods, counterfactuals, and concept attribution. The book concludes by showing how data effects interpretability;

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Statistical Models in S

, generalized linear models, additive models, local regression, and tree-based models. The contributions of the ten authors-most of whom work in the;

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Quantitative Intelligence Analysis

Quantitative Intelligence Analysis describes the model-based method of intelligence analysis that represents the analyst's mental models;

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Quantitative Intelligence Analysis

Quantitative Intelligence Analysis describes the model-based method of intelligence analysis that represents the analyst's mental models;

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Trends in Mathematics and Computational Intelligence

intelligence based on subsymbolic knowledge representation. Important research topics are focused on developing the interaction between computational;

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Fuzzy Sets-Based Methods and Techniques for Modern Analytics

valuable resource for researchers, data scientists and practitioners dealing with computational-intelligence-based optimization models for;

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Computational Intelligence for Business Analytics

of computational intelligence- based techniques. This book opens a new avenues in these subjects, identifies key developments and opportunities. The book;

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Advances in Computational Intelligence

This book presents the proceedings of the International Conference on Computational Intelligence 2018 (ICCI 2018). It brings together work;

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Computational Intelligence and Mathematics for Tackling Complex Problems 3

, based on traditional computer science science and the initial approaches of artificial intelligence are often referred to as biologically;

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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Confidence Intervals in Generalized Regression Models

generalized regression model (GRM)-of various types of regression models. It also uses a likelihood-based approach for performing statistical;

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Artificial Intelligence for Computational Modeling of the Heart

Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and;

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Computational Neuroscience for Advancing Artificial Intelligence

Computational Neuroscience for Advancing Artificial Intelligence: Models, Methods and Applications captures the latest research in this;

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Ordered Regression Models

well as variations based on the application of the parallel regression assumption. The authors first introduce the three parallel ordered;

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Ordered Regression Models

well as variations based on the application of the parallel regression assumption. The authors first introduce the three parallel;

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Regression And Time Series Model Selection

wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are;

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Modeling Steel and Composite Structures

Modeling Steel and Composite Structures explains the computational tools, methods and procedures used to design steel and composite;

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Agent-Based Computational Economics

This book aims to answer two questions that are fundamental to the study of agent-based economic models: what is agent-based computational;

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Militarized Conflict Modeling Using Computational Intelligence

Militarized Conflict Modeling Using Computational Intelligence examines the application of computational intelligence methods to model;

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Swarm Intelligence Methods for Statistical Regression

Intelligence Methods for Statistical Regression describes methods from the field of computational swarm intelligence (SI), and how they can be used to;

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