Author: Dawn E. Holmes
Publisher: Springer Science & Business Media
ISBN: 3642231519
Category : Technology & Engineering
Languages : en
Pages : 367
Book Description
There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
Data Mining: Foundations and Intelligent Paradigms
Author: Dawn E. Holmes
Publisher: Springer Science & Business Media
ISBN: 3642231519
Category : Technology & Engineering
Languages : en
Pages : 367
Book Description
There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
Publisher: Springer Science & Business Media
ISBN: 3642231519
Category : Technology & Engineering
Languages : en
Pages : 367
Book Description
There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
Data Mining: Foundations and Intelligent Paradigms
Author: Dawn E. Holmes
Publisher: Springer Science & Business Media
ISBN: 3642232418
Category : Technology & Engineering
Languages : en
Pages : 257
Book Description
There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 2: Core Topics including Statistical, Time-Series and Bayesian Analysis” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
Publisher: Springer Science & Business Media
ISBN: 3642232418
Category : Technology & Engineering
Languages : en
Pages : 257
Book Description
There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 2: Core Topics including Statistical, Time-Series and Bayesian Analysis” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
Data mining: foundations and intelligent paradigms
Author: Dawn E. Holmes
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Advances in Intelligent Signal Processing and Data Mining
Author: Petia Georgieva
Publisher: Springer
ISBN: 3642286968
Category : Technology & Engineering
Languages : en
Pages : 359
Book Description
The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms.
Publisher: Springer
ISBN: 3642286968
Category : Technology & Engineering
Languages : en
Pages : 359
Book Description
The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms.
Proceedings of the International Conference on Intelligent Computing, Communication and Information Security
Author: Vladan Devedzic
Publisher: Springer Nature
ISBN: 981991373X
Category : Technology & Engineering
Languages : en
Pages : 467
Book Description
This book contains high quality research papers accepted and presented at the International Conference on Intelligent Computing, Communication and Information Security (ICICCIS 2022), organized by Swami Keshvanand Institute of Technology, Management & Gramothan (SKIT), Jaipur, India during 25-26, November 2022. It presents the solutions of issues and challenges in intelligent computing, communication and information security domains. This book provides a background to problem domains, considering the progress so far, assessing the potential of such approaches, and exploring possible future directions as a single readily accessible source.
Publisher: Springer Nature
ISBN: 981991373X
Category : Technology & Engineering
Languages : en
Pages : 467
Book Description
This book contains high quality research papers accepted and presented at the International Conference on Intelligent Computing, Communication and Information Security (ICICCIS 2022), organized by Swami Keshvanand Institute of Technology, Management & Gramothan (SKIT), Jaipur, India during 25-26, November 2022. It presents the solutions of issues and challenges in intelligent computing, communication and information security domains. This book provides a background to problem domains, considering the progress so far, assessing the potential of such approaches, and exploring possible future directions as a single readily accessible source.
Handbook on Decision Making
Author: Jie Lu
Publisher: Springer Science & Business Media
ISBN: 3642257550
Category : Technology & Engineering
Languages : en
Pages : 457
Book Description
This book presents innovative theories, methodologies, and techniques in the field of risk management and decision making. It introduces new research developments and provides a comprehensive image of their potential applications to readers interested in the area. The collection includes: computational intelligence applications in decision making, multi-criteria decision making under risk, risk modelling,forecasting and evaluation, public security and community safety, risk management in supply chain and other business decision making, political risk management and disaster response systems. The book is directed to academic and applied researchers working on risk management, decision making, and management information systems.
Publisher: Springer Science & Business Media
ISBN: 3642257550
Category : Technology & Engineering
Languages : en
Pages : 457
Book Description
This book presents innovative theories, methodologies, and techniques in the field of risk management and decision making. It introduces new research developments and provides a comprehensive image of their potential applications to readers interested in the area. The collection includes: computational intelligence applications in decision making, multi-criteria decision making under risk, risk modelling,forecasting and evaluation, public security and community safety, risk management in supply chain and other business decision making, political risk management and disaster response systems. The book is directed to academic and applied researchers working on risk management, decision making, and management information systems.
Data Preprocessing in Data Mining
Author: Salvador García
Publisher: Springer
ISBN: 3319102478
Category : Technology & Engineering
Languages : en
Pages : 327
Book Description
Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.
Publisher: Springer
ISBN: 3319102478
Category : Technology & Engineering
Languages : en
Pages : 327
Book Description
Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.
Between Certainty and Uncertainty
Author: Ludomir M. Laudański
Publisher: Springer Science & Business Media
ISBN: 364225697X
Category : Mathematics
Languages : en
Pages : 314
Book Description
„Between Certainty & Uncertainty” is a one-of–a-kind short course on statistics for students, engineers and researchers. It is a fascinating introduction to statistics and probability with notes on historical origins and 80 illustrative numerical examples organized in the five units: · Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics . · Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. · Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient? · Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. · Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics . · Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. · Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient? · Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.
Publisher: Springer Science & Business Media
ISBN: 364225697X
Category : Mathematics
Languages : en
Pages : 314
Book Description
„Between Certainty & Uncertainty” is a one-of–a-kind short course on statistics for students, engineers and researchers. It is a fascinating introduction to statistics and probability with notes on historical origins and 80 illustrative numerical examples organized in the five units: · Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics . · Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. · Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient? · Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. · Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics . · Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. · Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient? · Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.
Data Mining: Foundations and Intelligent Paradigms
Author: Dawn E. Holmes
Publisher: Springer Science & Business Media
ISBN: 3642231667
Category : Technology & Engineering
Languages : en
Pages : 341
Book Description
There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
Publisher: Springer Science & Business Media
ISBN: 3642231667
Category : Technology & Engineering
Languages : en
Pages : 341
Book Description
There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing
Author: Hime Aguiar e Oliveira Junior
Publisher: Springer Science & Business Media
ISBN: 364227479X
Category : Technology & Engineering
Languages : en
Pages : 210
Book Description
Stochastic global optimization is a very important subject, that has applications in virtually all areas of science and technology. Therefore there is nothing more opportune than writing a book about a successful and mature algorithm that turned out to be a good tool in solving difficult problems. Here we present some techniques for solving several problems by means of Fuzzy Adaptive Simulated Annealing (Fuzzy ASA), a fuzzy-controlled version of ASA, and by ASA itself. ASA is a sophisticated global optimization algorithm that is based upon ideas of the simulated annealing paradigm, coded in the C programming language and developed to statistically find the best global fit of a nonlinear constrained, non-convex cost function over a multi-dimensional space. By presenting detailed examples of its application we want to stimulate the reader’s intuition and make the use of Fuzzy ASA (or regular ASA) easier for everyone wishing to use these tools to solve problems. We kept formal mathematical requirements to a minimum and focused on continuous problems, although ASA is able to handle discrete optimization tasks as well. This book can be used by researchers and practitioners in engineering and industry, in courses on optimization for advanced undergraduate and graduate levels, and also for self-study.
Publisher: Springer Science & Business Media
ISBN: 364227479X
Category : Technology & Engineering
Languages : en
Pages : 210
Book Description
Stochastic global optimization is a very important subject, that has applications in virtually all areas of science and technology. Therefore there is nothing more opportune than writing a book about a successful and mature algorithm that turned out to be a good tool in solving difficult problems. Here we present some techniques for solving several problems by means of Fuzzy Adaptive Simulated Annealing (Fuzzy ASA), a fuzzy-controlled version of ASA, and by ASA itself. ASA is a sophisticated global optimization algorithm that is based upon ideas of the simulated annealing paradigm, coded in the C programming language and developed to statistically find the best global fit of a nonlinear constrained, non-convex cost function over a multi-dimensional space. By presenting detailed examples of its application we want to stimulate the reader’s intuition and make the use of Fuzzy ASA (or regular ASA) easier for everyone wishing to use these tools to solve problems. We kept formal mathematical requirements to a minimum and focused on continuous problems, although ASA is able to handle discrete optimization tasks as well. This book can be used by researchers and practitioners in engineering and industry, in courses on optimization for advanced undergraduate and graduate levels, and also for self-study.