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Author: Kurt Varmuza
Publisher: Springer Science & Business Media
ISBN: 3642931553
Category : Science
Languages : en
Pages : 232
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Book Description
Analytical chemistry of the recent years is strongly influenced by automation. Data acquisition from analytica~ instruments - and some times also controlling of instruments - by a computer are principally solved since many years. Availability of microcomputers made these tasks also feasible from the economic point of view. Besides these basic applications of computers in chemical measurements scientists developed computer programs for solving more sophisticated problems for which some kind of "intelligence" is usually supposed to be necessary. Harm less numerical experiments on this topic led to passionate discussions about the theme "which jobs cannot be done by a computer but only by human brain ?~. If this question is useful at all it should not be ans wered a priori. Application of computers in chemistry is a matter of utility, sometimes it is a social problem, but it is never a question of piety for the human brain. Automated instruments and the necessity to work on complex pro blems enhanced the development of automatic methods for the reduction and interpretation of large data sets. Numerous methods from mathematics, statistics, information theory, and computer science have been exten sively investigated for the elucidation of chemical information; a new discipline "chemometrics" has been established. Three different approaches have been used for computer-assisted interpretations of chemical data. 1. Heuristic methods try to formu late computer programs working in a similar way as a chemist would solve the problem. 2.
Author: Kurt Varmuza
Publisher: Springer Science & Business Media
ISBN: 3642931553
Category : Science
Languages : en
Pages : 232
Get Book Here
Book Description
Analytical chemistry of the recent years is strongly influenced by automation. Data acquisition from analytica~ instruments - and some times also controlling of instruments - by a computer are principally solved since many years. Availability of microcomputers made these tasks also feasible from the economic point of view. Besides these basic applications of computers in chemical measurements scientists developed computer programs for solving more sophisticated problems for which some kind of "intelligence" is usually supposed to be necessary. Harm less numerical experiments on this topic led to passionate discussions about the theme "which jobs cannot be done by a computer but only by human brain ?~. If this question is useful at all it should not be ans wered a priori. Application of computers in chemistry is a matter of utility, sometimes it is a social problem, but it is never a question of piety for the human brain. Automated instruments and the necessity to work on complex pro blems enhanced the development of automatic methods for the reduction and interpretation of large data sets. Numerous methods from mathematics, statistics, information theory, and computer science have been exten sively investigated for the elucidation of chemical information; a new discipline "chemometrics" has been established. Three different approaches have been used for computer-assisted interpretations of chemical data. 1. Heuristic methods try to formu late computer programs working in a similar way as a chemist would solve the problem. 2.
Author: Richard G. Brereton
Publisher: John Wiley & Sons
ISBN: 0470987251
Category : Science
Languages : en
Pages : 532
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Book Description
Over the past decade, pattern recognition has been one of the fastest growth points in chemometrics. This has been catalysed by the increase in capabilities of automated instruments such as LCMS, GCMS, and NMR, to name a few, to obtain large quantities of data, and, in parallel, the significant growth in applications especially in biomedical analytical chemical measurements of extracts from humans and animals, together with the increased capabilities of desktop computing. The interpretation of such multivariate datasets has required the application and development of new chemometric techniques such as pattern recognition, the focus of this work. Included within the text are: ‘Real world’ pattern recognition case studies from a wide variety of sources including biology, medicine, materials, pharmaceuticals, food, forensics and environmental science; Discussions of methods, many of which are also common in biology, biological analytical chemistry and machine learning; Common tools such as Partial Least Squares and Principal Components Analysis, as well as those that are rarely used in chemometrics such as Self Organising Maps and Support Vector Machines; Representation in full colour; Validation of models and hypothesis testing, and the underlying motivation of the methods, including how to avoid some common pitfalls. Relevant to active chemometricians and analytical scientists in industry, academia and government establishments as well as those involved in applying statistics and computational pattern recognition.
Author: Jahan B. Ghasemi
Publisher: Elsevier
ISBN: 0323907067
Category : Science
Languages : en
Pages : 212
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Book Description
Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introductory approaches with the latest advanced techniques. Beginning with an introduction of univariate and multivariate statistical analysis, the book then explores multivariate calibration and validation methods. Soft modeling in chemical data analysis, hyperspectral data analysis, and autoencoder applications in analytical chemistry are then discussed, providing useful examples of the techniques in chemistry applications. Drawing on the knowledge of a global team of researchers, this book will be a helpful guide for chemists interested in developing their skills in multivariate data and error analysis. - Provides an introductory overview of statistical methods for the analysis and interpretation of chemical data - Discusses the use of machine learning for recognizing patterns in multidimensional chemical data - Identifies common sources of multivariate errors
Author: Lior Rokach
Publisher: World Scientific
ISBN: 9814271071
Category : Computers
Languages : en
Pages : 242
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Book Description
1. Introduction to pattern classification. 1.1. Pattern classification. 1.2. Induction algorithms. 1.3. Rule induction. 1.4. Decision trees. 1.5. Bayesian methods. 1.6. Other induction methods -- 2. Introduction to ensemble learning. 2.1. Back to the roots. 2.2. The wisdom of crowds. 2.3. The bagging algorithm. 2.4. The boosting algorithm. 2.5. The AdaBoost algorithm. 2.6. No free lunch theorem and ensemble learning. 2.7. Bias-variance decomposition and ensemble learning. 2.8. Occam's razor and ensemble learning. 2.9. Classifier dependency. 2.10. Ensemble methods for advanced classification tasks -- 3. Ensemble classification. 3.1. Fusions methods. 3.2. Selecting classification. 3.3. Mixture of experts and meta learning -- 4. Ensemble diversity. 4.1. Overview. 4.2. Manipulating the inducer. 4.3. Manipulating the training samples. 4.4. Manipulating the target attribute representation. 4.5. Partitioning the search space. 4.6. Multi-inducers. 4.7. Measuring the diversity -- 5. Ensemble selection. 5.1. Ensemble selection. 5.2. Pre selection of the ensemble size. 5.3. Selection of the ensemble size while training. 5.4. Pruning - post selection of the ensemble size -- 6. Error correcting output codes. 6.1. Code-matrix decomposition of multiclass problems. 6.2. Type I - training an ensemble given a code-matrix. 6.3. Type II - adapting code-matrices to the multiclass problems -- 7. Evaluating ensembles of classifiers. 7.1. Generalization error. 7.2. Computational complexity. 7.3. Interpretability of the resulting ensemble. 7.4. Scalability to large datasets. 7.5. Robustness. 7.6. Stability. 7.7. Flexibility. 7.8. Usability. 7.9. Software availability. 7.10. Which ensemble method should be used?
Author:
Publisher:
ISBN:
Category : Environmental health
Languages : en
Pages : 1028
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Book Description
Author: Chi Hau Chen
Publisher: World Scientific
ISBN: 9814497649
Category : Computers
Languages : en
Pages : 1045
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Book Description
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.
Author: P. Griffiths
Publisher: Springer Science & Business Media
ISBN: 1468424033
Category : Science
Languages : en
Pages : 395
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Book Description
The application of the Fourier transform is being seen to an increasing extent in all branches of chemistry, but it is in the area of chemical analysis that the greatest activity is taking place. Fourier transform infrared and nuclear magnetic resonance spectrometry are already routine methods for obtaining high-sensitivity IR and NMR spectra. Analogous methods are now being developed for mass spectrometry (Fourier transform ion cyclo tron resonance spectrometry) and microwave spectroscopy, and Fourier transform techniques have been successfully applied in several areas of electrochemistry. In addition the fast Fourier transform algorithm has been used for smoothing, interpolation, and more efficient storage of data, and has been studied as a potential method for more efficient identification of samples using pattern recognition techniques. Linear transforms have also been shown to be useful in analytical chemistry. Probably the most important of these is the Hadamard transform, which has been applied in alternative methods for obtaining IR and NMR data at high sensitivity. Even though measurements involving this algorithm will probably not be applied as universally as their Fourier transform ana logs, in the area of pattern recognition application of the Hadamard trans form will in all probability prove more important than application of the Fourier transform.
Author: Yolanda Pico
Publisher: Academic Press
ISBN: 0123848636
Category : Technology & Engineering
Languages : en
Pages : 813
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Book Description
Chemical Analysis of Food: Techniques and Applications reviews new technology and challenges in food analysis from multiple perspectives: a review of novel technologies being used in food analysis, an in-depth analysis of several specific approaches, and an examination of the most innovative applications and future trends. This book won a 2012 PROSE Award Honorable Mention in Chemistry and Physics from the Association of American Publishers. The book is structured in two parts: the first describes the role of the latest developments in analytical and bio-analytical techniques and the second reviews the most innovative applications and issues in food analysis. Each chapter is written by experts on the subject and is extensively referenced in order to serve as an effective resource for more detailed information. The techniques discussed range from the non-invasive and non-destructive, such as infrared spectroscopy and ultrasound, to emerging areas such as nanotechnology, biosensors and electronic noses and tongues. Important tools for problem-solving in chemical and biological analysis are discussed in detail. - Winner of a PROSE Award 2012, Book: Honorable Mention in Physical Sciences and Mathematics - Chemistry and Physics from the American Association of Publishers - Provides researchers with a single source for up-to-date information in food analysis - Single go-to reference for emerging techniques and technologies - Over 20 renowned international contributors - Broad coverage of many important techniques makes this reference useful for a range of food scientists
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 980
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Book Description
Author: Christopher M. Bishop
Publisher: Springer
ISBN: 9781493938438
Category : Computers
Languages : en
Pages : 0
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Book Description
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
