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Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)
Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)

In the early days of pattern recognition and statistical data analysis life was rather simple: datasets were relatively small, collected from well-designed experiments, analyzed using a few methods that had good theoretical background. Explosive growth of the use of computers led to the creation of huge amounts of data of all kinds,...

Advanced Computer-Assisted Techniques in Drug Discovery (Methods and Principles in Medicinal Chemistry)
Advanced Computer-Assisted Techniques in Drug Discovery (Methods and Principles in Medicinal Chemistry)
The main objective of this series is to offer a practice-oriented survey of techniques currently used in Medicinal Chemistry. Following the volumes on Hansch analysis and related approaches (Vol. 1) and multivariate analyses (Vol. 2), the present handbook focuses on some new, emerging techniques in drug discovery; emphasis is...
SPSS for Starters, Part 2 (SpringerBriefs in Statistics)
SPSS for Starters, Part 2 (SpringerBriefs in Statistics)
The small book ‘‘SPSS for Starters’’ issued in 2010 presented 20 chapters of cookbook like step by step data-analyses of clinical research, and was written to help clinical investigators and medical students analyze their data without the help of a statistician. The book served its purpose well enough, since...
Statistical Methods in Analytical Chemistry (Chemical Analysis: A Series of Monographs on Analytical Chemistry and Its Applications)
Statistical Methods in Analytical Chemistry (Chemical Analysis: A Series of Monographs on Analytical Chemistry and Its Applications)

This new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments. Complete with examples from the chemical and pharmaceutical laboratory and manufacturing areas, this thoroughly updated book clearly...

Spectrochemical Analysis Using Infrared Multichannel Detectors
Spectrochemical Analysis Using Infrared Multichannel Detectors
A tremendous growth in the utilization of multichannel detectors for infrared (IR) spectroscopy has been observed over the past decade. In some cases, the incorporation of multichannel detectors has significantly changed the practice of IR spectroscopy; while in others, it has provided new opportunities for spectroscopic...
Kernel Smoothing (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
Kernel Smoothing (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel function.

This book provides uninitiated readers with a feeling for the principles, applications, and analysis of kernel smoothers.
...

Bayesian Models for Categorical Data (Wiley Series in Probability and Statistics)
Bayesian Models for Categorical Data (Wiley Series in Probability and Statistics)

The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike. Emphasizing the use of statistical...

Nonlinear Biomedical Signal Processing, Fuzzy Logic, Neural Networks, and New Algorithms (IEEE Press Series on Biomedical Engineering) (Volume 1)
Nonlinear Biomedical Signal Processing, Fuzzy Logic, Neural Networks, and New Algorithms (IEEE Press Series on Biomedical Engineering) (Volume 1)

For the first time, eleven experts in the fields of signal processing and biomedical engineering have contributed to an edition on the newest theories and applications of fuzzy logic, neural networks, and algorithms in biomedicine. Nonlinear Biomedical Signal Processing, Volume I provides comprehensive coverage of nonlinear signal...

Approximation Methods for Polynomial Optimization: Models, Algorithms, and Applications (SpringerBriefs in Optimization)
Approximation Methods for Polynomial Optimization: Models, Algorithms, and Applications (SpringerBriefs in Optimization)
Polynomial optimization, as its name suggests, is used to optimize a generic multivariate polynomial function, subject to some suitable polynomial equality and/or inequality constraints. Such problem formulation dates back to the nineteenth century when the relationship between nonnegative polynomials and sum of squares (SOS) was...
Internet Success: A Study of Open-Source Software Commons
Internet Success: A Study of Open-Source Software Commons

The use of open-source software (OSS)--readable software source code that can be copied, modified, and distributed freely--has expanded dramatically in recent years. The number of OSS projects hosted on SourceForge.net (the largest hosting Web site for OSS), for example, grew from just over 100,000 in 2006 to more than 250,000 at the...

Software Reliability Modeling: Fundamentals and Applications (SpringerBriefs in Statistics)
Software Reliability Modeling: Fundamentals and Applications (SpringerBriefs in Statistics)

Software reliability is one of the most important characteristics of software product quality. Its measurement and management technologies during the software product life cycle are essential to produce and maintain quality/reliable software systems. Part 1 of this book introduces several aspects of software reliability modeling and its...

Statistics and Data Analysis for Financial Engineering (Springer Texts in Statistics)
Statistics and Data Analysis for Financial Engineering (Springer Texts in Statistics)

Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and...

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