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SPIRES-BOOKS: FIND KEYWORD DATA MINING AND KNOWLEDGE DISCOVERY *END*INIT* use /tmp/qspiwww.webspi1/7103.32 QRY 131.225.70.96 . find keyword data mining and knowledge discovery ( in books using www Cover
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Call number:9783319459011:ONLINE Show nearby items on shelf
Title:First Complex Systems Digital Campus World E-Conference 2015
Author(s):
Date:2017
Size:1 online resource (VIII, 424 p. 120 illus., 96 illus. in color p.)
Contents:Welcome to CS-DC’15 -- Reconstructing multi-scale dynamics -- Machine learning methods -- A formal model to compute uncertain continuous data -- Knowledge maps -- Analysis of a Planetary Scale Scientific Collaboration Dataset Reveals
Novel Patterns -- Epistemology of integrative and predictive sciences -- Information science and the complexity: are we orientated to a transdisciplinary science? -- Synthesis of ecology, biology and ethnographic data -- Bayesian
Causalities, Mappings, and Phylogenies: A Social Science Gateway for Modeling Complexity in Ethnographic, Archaeo-, Eco- and Bio-logical Variables -- Multi-level modeling -- Statistical and dynamical properties of networks -- Community
detection as an efficient way to attack real networks -- From particles to complex matter -- Chemical garden -- Assembly of molecular metal oxides from the nano to the macroscale via chemical gardens -- Physics of complex systems --
Viscosity scaling in hydrodynamic instabilities in porous media -- A general approach to the linear stability analysis of miscible viscous fingering in porous media -- From individual to social cognition -- From individual to social
cognition: Piaget, Jung and commons -- Ecological approach of sport and sport education -- Ecological Dynamics: a theoretical framework for understanding sport performance, physical education and physical -- Emerging dance movements
under ecological constraints in Contact Improvisation dancers with different background -- Emerging collective shared behaviors from individual exploration in football small-sided games -- Adaptability in swimming pattern: how do
swimmers adapt propulsive action as a function of speed? -- Backstroke start performance prediction -- Flexible perception-action strategies for follow-the-leader coordination -- Dynamic process of pulmonary data analysis: from the
athlete mouth to the coach’s hands -- From processing units to computational ecosystems to the cloud -- A multi-agent system approach to load-balancing and resource allocation for distributed computing -- Integrative science of
education -- POEM-COPA Collaborative Open Peer Assessment -- Implications of agent-based computational modeling and simulation for preventive education in children with ADHD -- MOOC as a complex system -- From fields to territories to
the planet -- Integrative logistics -- Logistics and Territory integrative approach -- Process modeling of an international transport chain through the simulation tool SIMPROCESS -- Dynamic emissions reduction from vehicles with
technical and behavioral approach -- 4p-factories (e-lab) -- Is the Lean Organisation a complex system? -- An artificial immune ecosystem model for hybrid cloud supervision -- Engineering of territory sustainability -- Spatialisation
of Soil Erosion Susceptibility Using USLE Model -- Social patterns in multicultural environments Matrimonial patterns and trans-ethnic entities -- Economics as a complex evolutionist system -- A study of heterogeneity in a stock market
simulator based on a model of agents that learn from experience in a market with multiple stocks -- Are innovation systems complex systems? -- From molecules to ecosphere -- Ocean biogeochemical dynamics -- Frontal systems as
mechanisms of fish aggregation -- Lagrangian approach to phytoplankton mesoscale biogeography in the Kerguelen region -- Lyapunov exponents and oceanic fronts.
ISBN:9783319459011
Series:eBooks
Series:Springer eBooks
Series:Springer 2017 package
Keywords: Physics , Data mining , System theory , Computational intelligence , Complexity, Computational , Physics , Complex Systems , Complex Systems , Complexity , Data Mining and Knowledge Discovery , Computational Intelligence , Biological and Medical Physics, Biophysics
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Call number:SPRINGER-2016-9783319292281:ONLINE Show nearby items on shelf
Title:Proceedings of ECCS 2014 European Conference on Complex Systems
Author(s):
Date:2016
Size:1 online resource (48 p.)
Note:10.1007/978-3-319-29228-1
Contents:Preface -- Detection of Non-Self-Correcting Nature of Information Cascade -- Fitting Planar Proximity Graphs on Real Street Networks. - Qualitative Methods for the Exploration of Complexity in Human Social Systems: Applications in
Family Psychology -- Tangible Networks: A Toolkit for Exploring Network Science -- The Geometric Origins of Complex Cities -- Revealing the Relation Between Structure of Chloroplast Genomes and Host Taxonomy -- Complex Synchronization
Patterns in the Human Connectome Network -- Structure of a Media Co-Occurrence Network -- Spatial Effects of Delay-induced Stochastic Oscillations in a Multi-Scale Cellular System -- An Agent-Based Modelling Approach to Biological
Invasion by Macroalgae in European Coastal Environments -- Characterisation of the Idiotypic Immune Network through Persistent Entropy -- Interests Propagation in Computer Science Research Community -- Nonparametric Estimation of the
Preferential Attachment Function in Complex Networks: Evidence of Deviations from Log Linearity -- N-Gram Events for Analysis of Financial Time Series -- Human Mobility and the Dynamics of Measles in Large Geographical Areas -- Does
Training Lead to the Formation of Modules in Threshold Networks? -- Understanding Financial News with Multi-layer Network Analysis -- Channel-Specic Daily Patterns in Mobile Phone Communication -- Investigating the Phonetic
Organisation of the English Language via Phonological Networks, Percolation and Markov Models -- An Agent-Based Model for Agricultural Supply Chains: the Case of Uganda -- Chimera States in Neuronal Systems of Excitability type-I --
Multiobjective Optimization and Phase Transitions -- Power Laws as Statistical Mixtures -- A Network-Based Analysis of the European Emission Market -- Dynamics of Commodity Price Fluctuations in Japan -- Understanding the Diffusion of
YouTube Videos -- Free Energy Rate Density and Self-organization in Complex Systems
ISBN:9783319292281
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Physics , Data mining , System theory , Complexity, Computational , Physics , Complex Networks , Complexity , Complex Systems , Data Mining and Knowledge Discovery
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Call number:SPRINGER-2016-9783319287096:ONLINE Show nearby items on shelf
Title:Data Mining with SPSS Modeler Theory, Exercises and Solutions
Author(s): Tilo Wendler
Date:2016
Size:1 online resource (1277 p.)
Note:10.1007/978-3-319-28709-6
Contents:Preface -- Introduction -- Basic Functions of the SPSS Modeler -- Univariate Statistics -- Multivariate Statistics -- Regression Models -- Factor Analysis -- Cluster Analysis -- Classification Models -- Using R with the Modeler -- Data Sets Used in This Book
ISBN:9783319287096
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Data mining , Computer software , Statistics , Statistical Theory and Methods , Statistics and Computing/Statistics Programs , Data Mining and Knowledge Discovery , Mathematical Software
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Call number:SPRINGER-2016-9783319263892:ONLINE Show nearby items on shelf
Title:First-stage LISA Data Processing and Gravitational Wave Data Analysis Ultraprecise Inter-satellite Laser Ranging, Clock Synchronization and Novel Gravitational Wave Data Analysis Algorithms
Author(s): Yan Wang
Date:2016
Edition:1st ed. 2016
Size:1 online resource (1 p.)
Note:10.1007/978-3-319-26389-2
Contents:Introduction -- LISA data processing chain -- Applying the Kalman filter to a simple case -- The inter-spacecraft measurements -- Design a hybrid extended Kalman filter for the entire LISA constellation -- Alternative Kalman filter
models -- Broken laser links and robustness -- Optimal filtering for LISA with effective system models -- Clock noise and disordered measurements -- Octahedron configuration for a displacement noise-canceling gravitational wave
detector in space -- EMRI data analysis with a phenomenological waveform -- Fast detection and automatic parameter estimation of a gravitational wave signal with a novel method -- Likelihood transform: making optimization and parameter
estimation easier.
ISBN:9783319263892
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Physics , Data mining , Gravitation , Astrophysics , Quantum optics , Lasers , Photonics , Physical measurements , Measurement , Physics , Astrophysics and Astroparticles , Laser Technology, Photonics , Data Mining and Knowledge Discovery , Classical and Quantum Gravitation, Relativity Theory , Measurement Science and Instrumentation , Quantum Optics
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Call number:SPRINGER-2014-9783319015958:ONLINE Show nearby items on shelf
Title:Data Analysis, Machine Learning and Knowledge Discovery [electronic resource]
Author(s): Myra Spiliopoulou
Lars Schmidt-Thieme
Ruth Janning
Date:2014
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:Data analysis, machine learning and knowledge discovery are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be appliedto a vast set of app lications such as web and text mining, marketing, medicine, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning andknowledge discovery presented during the 36th annual conference of the German Classification Society (GfKl). The conference was held at the University of Hildesheim (Germany) in August 2012
Contents:AREA Statistics and Data Analysis: Classifcation, Cluster Analysis, Factor Analysis and Model Selection
AREA Machine Learning and Knowledge Discovery: Clustering, Classifiers, Streams and Social Networks
AREA Data Analysis and Classification in Marketing
AREA Data Analysis in Finance
AREA Data Analysis in Biostatistics and Bioinformatics
AREA Interdisciplinary Domains: Data Analysis in Music, Education and Psychology
LIS Workshop: Workshop on Classification and Subject Indexing in Library and Information Science
ISBN:9783319015958
Series:eBooks
Series:SpringerLink
Series:Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Statistical methods , Mathematical statistics , Marketing , Philosophy (General)
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Call number:SPRINGER-2014-9781493907427:ONLINE Show nearby items on shelf
Title:Clusters, Orders, and Trees: Methods and Applications [electronic resource] : In Honor of Boris Mirkin's 70th Birthday
Author(s): Fuad Aleskerov
Boris Goldengorin
Panos M Pardalos
Date:2014
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:The volume is dedicated to Boris Mirkin on the occasion of his 70th birthday. In addition to his startling PhD results in abstract automata theory, Mirkins ground breaking contributions in various fields of decision making anddata analysis have marke d the fourth quarter of the 20th century and beyond.Mirkin has done pioneering work in group choice, clustering, data mining and knowledge discovery aimed at finding and describing non-trivial or hiddenstructuresfirst of all, clusters, orderings, and hier archiesin multivariate and/or network data. This volume contains a collection of papers reflecting recent developments rooted inMirkin's fundamental contribution to thestate-of-the-art in group choice, ordering, clustering, data mining, and knowledge disc overy. Researchers, students, and software engineers will benefit from new knowledge discovery techniques and application directions
Contents:Three and One Questions to Dr. B. Mirkin about Complexity Statistics (I. Mandel)
Section 1
A Polynomial Algorithm for a Class of 0
1 Fractional Programming Problems Involving Composite Functions, with an Application to Additive Clustering (P. Hansen, C. Meyer)
Experiments with a Non
Convex Variance
Based Clustering Criterion (R.F. Toso, E.V. Bauman, C.A. Kulikowski, I.B. Muchnik)
Strategy
Proof Location Functions on Finite Graphs (F.R. McMorris, H.M. Mulder, F.S. Roberts)
A Pseudo
Boolean Approach to the Market Graph Analysis by Means of the p
Median Model (B. Goldengorin, A. Ko
ISBN:9781493907427
Series:eBooks
Series:SpringerLink
Series:Springer Optimization and Its Applications, 1931-6828 : v92
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computational complexity , Electronic data processing
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Call number:SPRINGER-2013-9783319000350:ONLINE Show nearby items on shelf
Title:Algorithms from and for Nature and Life [electronic resource] : Classification and Data Analysis
Author(s): Berthold Lausen
Dirk Van den Poel
Alfred Ultsch
Date:2013
Publisher:Cham : Springer International Publishing : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This volume provides approaches and solutions to challenges occurring at the interface of research fields such as, e.g., data analysis, data mining and knowledge discovery, computer science, operations research, and statistics. Inaddition to theory-o riented contributions various application areas are included. Moreover, traditional classification research directions concerning network data, graphs, and social relationships as well as statistical musicologydescribe examples for current interest fields tackled by the authors. The book comprises a total of 55 selected papers presented at the Joint Conference of the German Classification Society (GfKl),the German Association for PatternRecognition (DAGM), and the Symposium of the International Federation of Classification Societies (IFCS) in 2011
Note:Springer eBooks
Contents:Invited
Clustering and Unsupervised Learning
Statistical Data Analysis, Visualization and Scaling
Bioinformatics and Biostatistics
Archaeology and Geography, Psychology and Educational Sciences
Text Mining, Social Networks and Clustering
Banking and Finance
Marketing and Management
Music Classification Workshop
ISBN:9783319000350
Series:e-books
Series:SpringerLink (Online service)
Series:Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Social sciences Data processing , Mathematical statistics , Economics Statistics , Operations research
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Call number:SPRINGER-2012-9781461435204:ONLINE Show nearby items on shelf
Title:Statistical Challenges in Modern Astronomy V [electronic resource]
Author(s): Eric D Feigelson
G. Jogesh Babu
Date:2012
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Now beginning its third decade, the Statistical Challenges in Modern Astronomy (SCMA) conferences are the premier forums where astronomers and statisticians discuss advanced methodological issues arising in astronomical research.From cosmology to exo planets, astronomers produce enormous datasets and encounter difficult modeling issues to arrive at astrophysical insights. At the SCMA V conference held at Penn State University in June 2011, researchers fromaround the world presented the latest astrosta tistical methods. To promote cross-disciplinary perspectives, each lecture from an expert in one field is followed by a commentary from the other field. A wide range of statisticaldevelopments are highlighted in the SCMA V conference. Some focus on proble ms arising in precision cosmology involving characteristics of the cosmic microwave background, galaxy clustering and gravitational lensing. Bayesianapproaches are particularly important in this and other areas. Knowledge discovery from megadatasets bring s methods of data mining into use. Image analysis and time series analysis are areas where astronomers perennially wrestle withsophisticated modeling problems. The proceedings ends with discussion of the future of astrostatistics. Eric D. Feigelson, Profe ssor of Astronomy & Astrophysics, and G. Jogesh Babu, Professor of Statistics, have long collaboratedin cross-disciplinary research and services. Under the auspices of Penn State's Center for Astrostatistics, they run the SCMA conferences, offer summer sc hools in statistics for astronomers, produce texts and research articlespromoting advances in statistical methodology in astronomy. Feigelson also conducts research in X-ray astronomy and star formation, and Babu is a mathematical statistician with intere st in bootstrap methods, nonparametrics andasymptotic theory
Note:Springer eBooks
Contents:Statistics in Cosmology
Bayesian Analysis Across Astronomy
Data Mining and Astroinformatics
Image and Time Series Analysis
The Future of Astrostatistics
Contributed Papers
ISBN:9781461435204
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Statistics, 0930-0325 : v902
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics
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Call number:SPRINGER-2012-9781461421078:ONLINE Show nearby items on shelf
Title:Data Mining for Biomarker Discovery [electronic resource]
Author(s): Panos M Pardalos
Petros Xanthopoulos
Michalis Zervakis
Date:2012
Publisher:Boston, MA : Springer US
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Data Mining for Biomarker Discovery is designed to motivate collaboration and discussion among various disciplines and will be of interest to students and researchers in engineering, computer science, applied mathematics,medicine, and anyone interest ed in the interdisciplinary application of data mining techniques. Biomarker discovery is an important area of biomedical research that can lead to significant breakthroughs in disease analysis and targetedtherapy. Moreover, the discovery and management o f new biomarkers is a challenging and attractive problem in the emerging field of biomedical informatics. This volume is acollection of state-of-the-artresearch from selectparticipants of the International Conference on Biomedical Data and Knowledge Minin g: Towards Biomarker Discovery, held July 7-9, 2010 in Chania, Greece. Contributions focus on biomarker data integration, information retrievalmethods, and statistical machine learning techniques, all presented with new results, models, and algorithms
Note:Springer eBooks
Contents:Preface
1. Data Mining Strategies Applied in Brain Injury Models (S. Mondello, F. Kobeissy, I. Fingers, Z. Zhang, R.L. Hayes, K.K.W. Wang)
Application of Decomposition Methods in the Filtering of Event Related Potentials (K. Michalopoulos, V. Iordanidou, M. Zervakis)
3. EEG Features as Biomarkers for Discrimination of Pre
ictal states (A. Tsimpiris, D. Kugiumtzis)
4. Using Relative Power Asymmetry as a Biomarker for Classifying Psychogenic Non
epileptic Seizure and Complex Partial Seizure Patients (J.H. Chien, D
S. Shiau, J.C. Sackellares, J.J. Halford, K.M. Kelly, P.M. Pardalos)
ISBN:9781461421078
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Optimization and Its Applications, 1931-6828 : v65
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Biochemical engineering , Medical records Data processing , Data mining
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Call number:SPRINGER-2011-9783642133121:ONLINE Show nearby items on shelf
Title:Classification and Multivariate Analysis for Complex Data Structures [electronic resource]
Author(s): Bernard Fichet
Domenico Piccolo
Rosanna Verde
Maurizio Vichi
Date:2011
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends,and to automatically b ag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first JointMeeting of the Socit Francophone de Classifi cation and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and theapplicative point of views, in the fields of Clustering, Classificatio n, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics
Note:Springer eBooks
Contents:Key Notes
Classification and Discrimination
Data Mining
Robustness and Classification
Categorical Data and Latent Class Approach
Latent Variables and Related Methods
Symbolic, Multivalued and Conceptual Data Analysis
Spatial, Temporal, Streaming and Functional Data Analysis
Bio and Health Science
ISBN:9783642133121
Series:e-books
Series:SpringerLink (Online service)
Series:Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data structures (Computer science) , Computer science , Multimedia systems , Distribution (Probability theory) , Mathematical statistics
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Call number:SPRINGER-2011-9781441998903:ONLINE Show nearby items on shelf
Title:Data Mining with Rattle and R [electronic resource] : The Art of Excavating Data for Knowledge Discovery
Author(s): Graham Williams
Date:2011
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing datamining many decisions n eed to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the morepopular algorithms of data mining. With a fo cus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built onthe sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, modelevaluation, and practical deployment. The reader will learn to rapidly deliver a data mining proj ect using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data miningenvironment with all the power, and more, of the many commercial offerings
Note:Springer eBooks
Contents:Introduction
Getting Started
Working with Data
Loading Data
Exploring Data
Interactive Graphics
Transforming Data
Descriptive and Predictive Analytics
Cluster Analysis
Association Analysis
Decision Trees
Random Forests
Boosting
Support Vector Machines
Model Performance Evaluation
Deployment
ISBN:9781441998903
Series:e-books
Series:SpringerLink (Online service)
Series:Use R
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics
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Call number:SPRINGER-2010-9781441916303:ONLINE Show nearby items on shelf
Title:Data Mining and Knowledge Discovery via Logic-Based Methods [electronic resource] : Theory, Algorithms, and Applications
Author(s): Evangelos Triantaphyllou
Date:2010
Publisher:Boston, MA : Springer US
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The importance of having efficient and effective methods for data mining and knowledge discovery (DM) is rapidly growing. This is due to the wide use of fast and affordable computing power and data storage media and also thegathering of huge amounts of data in almost all aspects of human activity and interest. While numerous methods have been developed, the focus of this book presents algorithms and applications using one popular method that has beenformulated in terms of binary attributes, i.e., by Boolean functions defined on several attributes that are easily transformed into rules that can express new knowledge. This book presents methods that deal with key data mining andknowledge discovery issues in an intuitive manner, in a natural sequence, a nd in a way that can be easily understood and interpreted by a wide array of experts and end users. The presentation provides a unique perspective into theessence of some fundamental DM issues, many of which come from important real life applications such as breast cancer diagnosis. Applications and algorithms are accompanied by extensive experimental results and are presented in a waysuch that anyone with a minimum background in mathematics and computer science can benefit from the exposition. Rigor in m athematics and algorithmic development is not compromised and each chapter systematically offers some possibleextensions for future research
Note:Springer eBooks
Contents:Algorithmic Issues
Inferring a Boolean Function from Positive and Negative Examples
A Revised Branch
and
Bound Approach for Inferring a Boolean Function from Examples
Some Fast Heuristics for Inferring a Boolean Function from Examples
An Approach to Guided Learning of Boolean Functions
An Incremental Learning Algorithm for Inferring Boolean Functions
A Duality Relationship Between Boolean Functions in CNF and DNF Derivable from the Same Training Examples
The Rejectability Graph of Two Sets of Examples
Application Issues
The Reliability Issue in Data Mining: The Case
ISBN:9781441916303
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Optimization and Its Applications, 1931-6828 : v43
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer science , Operations research
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Call number:SPRINGER-2007-9783540735601:ONLINE Show nearby items on shelf
Title:Selected Contributions in Data Analysis and Classification [electronic resource]
Author(s): Paula Brito
Guy Cucumel
Patrice Bertrand
Francisco Carvalho
Date:2007
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This volume presents recent methodological developments in data analysis and classification. A wide range of topics is covered that includes methods for classification and clustering, dissimilarity analysis, graph analysis,consensus methods, conceptu al analysis of data, analysis of symbolic data, statistical multivariate methods, data mining and knowledge discovery in databases. Besides structural and theoretical results, the book presents a wide varietyof applications, in fields such as biology, mic ro-array analysis, cyber traffic, bank fraud detection, and text analysis. Combining new methodological advances with a wide variety of real applications, this volume is certainly ofspecial value for researchers and practitioners, providing new analytical tools that are useful in theoretical research and daily practice in classification and data analysis
Note:Springer eBooks
Contents:Analysis of Symbolic Data
Clustering Methods
Conceptual Analysis of Data
Consensus Methods
Data Analysis, Data Mining, and KDD
Dissimilarities: Structures and Indices
Multivariate Statistics
ISBN:9783540735601
Series:e-books
Series:SpringerLink (Online service)
Series:Studies in Classification, Data Analysis, and Knowledge Organization, 1431-8814
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Optical pattern recognition , Mathematical statistics
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Call number:SPRINGER-2005-9780387238302:ONLINE Show nearby items on shelf
Title:Handbook of Combinatorial Optimization [electronic resource] : Supplement Volume B
Author(s): Ding-Zhu Du
Panos M Pardalos
Date:2005
Publisher:Boston, MA : Springer US
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This is a supplementary volume to the major three-volume Handbook of Combinatorial Optimization set, as well as the Supplement Volume A. It can also be regarded as a stand-alone volume which presents chapters dealing with variousaspects of the subjec t, including optimization problems and algorithmic approaches for discrete problems. Audience This handbook is suitable for all those who use combinatorial optimization methods to model and solve problems
Note:Springer eBooks
Contents:Preface
Data Correcting Algorithms in Combinatorial Optimization
The Steiner Ratio of Banach
Minkowski Space
Probabilistic Verification and Non
Approximability
Steiner Trees in Industry
Network
Based Model and Algorithms in Data Mining and Knowledge Discovery
The Generalized Assignment Problem and Extensions
Optimal Rectangular Partitions
Connected Dominating Sets in Sensor Networks and MANETs
Author Index
Subject Index
ISBN:9780387238302
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Computer science , Systems theory , Combinatorics , Operations research
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Call number:SPRINGER-2002-9783642559914:ONLINE Show nearby items on shelf
Title:Classification, Automation, and New Media Proceedings of the 24th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Passau, March 15—17, 2000
Author(s):
Date:2002
Size:1 online resource (535 p.)
Note:10.1007/978-3-642-55991-4
Contents:1: Data Analysis, Statistics, and Classification -- Clustering and Models -- Some New and Some Old Results for the Polytomous Rasch Model -- Some Basic Results on the Extension of Quasi-likelihood Based Measurement Error Correction to
Multivariate and Flexible Structural Models -- On the Optimal Number of Clusters in Histogram Clustering -- The Dual Dynamic Factor Analysis Models -- Joint Non-symmetrical Correspondence Analysis with Ordered Categories -- Regression
Analysis of Extremely Multicollinear Data -- Modern Data Analysis: A Clash of Paradigms -- Two-mode Clustering with Genetic Algorithms -- Exact Tests for the Comparison of Binary Data Structures in Time -- Connected Maximum Split
Clustering of Ladder Graphs -- A Generalization of Two-mode Three-way Asymmetric Multidimensional Scaling -- Central Limit Theorem for Probabilities of Correct Classification -- A New Model for the Analysis of Multitrait-multimethod
Data -- Discrete and Continuous Models for Two-way Data -- 2: Pattern Recognition and Automation -- Towards Feature Fusion — A Classifier on the Basis of Automatically Generated Significant Contour Sections -- Convex Discriminant
Analysis Tools for Non Convex Pattern Recognition -- Sparse Kernel Feature Analysis -- 3: Data Mining, Information Processing, and Automation -- Exploring Association Rules by Interactive Graphics -- Classification of Texts with
Support Vector Machines: An Examination of the Efficiency of Kernels and Data-transformations -- Text Mining with the Help of Cohesion Trees -- New Features of Categorical Principal Components Analysis for Complicated Data Sets,
Including Data Mining -- Supplement of Information: Data Integration by Classification of Pairs of Records -- The Completion of Missing Values by Neural Nets for Data Mining -- Knowledge Landscapes: Clustering Hypermedia Course Content
for Efficient Overviews -- Simplification of Knowledge Discovery using “Structure Classification” -- 4: New Media, Web Mining, and Automation -- Natural Language-based Specification and Fuzzy Logic for the Multimedia Development
Process -- A Tool System for an Object-oriented Approach to Construction and Maintenance of Hypermedia Documents -- Recommendations for Virtual Universities from Observed User Behavior -- Virtual Dialect Areas in the Internet:
“Townchats” -- The Navigation Problem in the World-Wide-Web -- Mining Web Usage Data for Automatic Site Personalization -- Integrating Combinatorial Relationships in a Cartography for Web Site Promotion -- 5: Applications in Management
Science, Finance, and Marketing -- Common Due Date Scheduling — Straddling Jobs and Due Windows — -- Currency Derivatives in German Non-financials: Empirical Evidence on Theoretical Approaches -- Data Visualization and Preparation by
Separating Sales Force Data -- Fuzzy Scenario Evaluation -- Fair Stock Risk Premiums under Firm-specific Price Jumps -- What Components Determine Stock Market Returns in the 1990’s? -- A Comparison of Estimators for Multivariate ARCH
Models -- Pricing of a New Integrated Risk Reinsurance Product -- A Multiple Method Approach for Discrimination and Classification in Marketing Research -- Goodness-of-Fit Measures for Two-mode Cluster Analyses -- On Volatility
Transfers During the Asia Crisis in 1997-1998 -- 6: Applications in Medicine, Biology, Archaeology, and Others -- QTL Mapping in Plant Populations -- Robust Multivariate Methods in Geostatistics -- Resampling Methods in Physical
Mapping -- Validating Dialect Comparison Methods -- Rater Classification on the Basis of Latent Features in Responding to Situations -- Results of Automatic Conversion of Diagnoses from ICD-9 to ICD-10 for Cancer Registration --
Exploring Roman Brick and Tile by Cluster Analysis with Validation of Results -- Relief Intensity and the Formation of the Archaeological Record -- Spatio-Temporal Modeling of Cancer Mortality Rates -- The Classification of Critical
Periods for Melanoma Development due to UV-Radiation -- Classification in the Prescription of Medicaments -- Effects of Independent Non-differential Misclassification on the Attributable Risk -- A New Approach to Discriminant Analysis
with Longitudinal Data -- Author Index
ISBN:9783642559914
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Computer science , Information technology , Business , Data structures (Computer science) , Coding theory , Pattern recognition , Statistics , Econometrics , Computer Science , Data Structures, Cryptology and Information Theory , Coding and Information Theory , Econometrics , IT in Business , Statistics for Business/Economics/Mathematical Finance/Insurance , Pattern Recognition
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Call number:SPRINGER-1997-9783642979668:ONLINE Show nearby items on shelf
Title:Self-Organizing Maps
Author(s): Teuvo Kohonen
Date:1997
Edition:Second Edition
Size:1 online resource (426 p.)
Note:10.1007/978-3-642-97966-8
Contents:1. Mathematical Preliminaries -- 1.1 Mathematical Concepts and Notations -- 1.2 Distance Measures for Patterns -- 1.3 Statistical Pattern Recognition -- 1.4 The Subspace Methods of Classification -- 1.5 The Robbins-Monro Stochastic
Approximation -- 1.6 Dynamically Expanding Context -- 2. Justification of Neural Modeling -- 2.1 Models, Paradigms, and Methods -- 2.2 On the Complexity of Biological Nervous Systems -- 2.3 Relation Between Biological and Artificial
Neural Networks -- 2.4 What Functions of the Brain Are Usually Modeled? -- 2.5 When Do We Have to Use Neural Computing? -- 2.6 Transformation, Relaxation, and Decoder -- 2.7 Categories of ANNs -- 2.8 Competitive-Learning Networks --
2.9 Three Phases of Development of Neural Models -- 2.10 A Simple Nonlinear Dynamic Model of the Neuron -- 2.11 Learning Laws -- 2.12 Brain Maps -- 3. The Basic SOM -- 3.1 The SOM Algorithm in the Euclidean Space -- 3.2 The
“Dot-Product SOM” -- 3.3 Preliminary Demonstrations of Topology-Preserving Mappings -- 3.4 Basic Mathematical Approaches to Self-Organization -- 3.5 Initialization of the SOM Algorithms -- 3.6 On the “Optimal” Learning-Rate Factor --
3.7 Effect of the Form of the Neighborhood Function -- 3.8 Magnification Factor -- 3.9 Practical Advice for the Construction of Good Maps -- 3.10 Examples of Data Analyses Implemented by the SOM -- 3.11 Using Gray Levels to Indicate
Clusters in the SOM -- 3.12 Derivation of the SOM Algorithm in the General Metric -- 3.13 What Kind of SOM Actually Ensues from the Distortion Measure? -- 3.14 Batch Computation of the SOM (“Batch Map”) -- 3.15 Further Speedup of SOM
Computation -- 4. Physiological Interpretation of SOM -- 4.1 Two Different Lateral Control Mechanisms -- 4.2 Learning Equation -- 4.3 System Models of SOM and Their Simulations -- 4.4 Recapitulation of the Features of the Physiological
SOM Model -- 5. Variants of SOM -- 5.1 Overview of Ideas to Modify the Basic SOM -- 5.2 Adaptive Tensorial Weights -- 5.3 Tree-Structured SOM in Searching -- 5.4 Different Definitions of the Neighborhood -- 5.5 Neighborhoods in the
Signal Space -- 5.6 Dynamical Elements Added to the SOM -- 5.7 Operator Maps -- 5.8 Supervised SOM -- 5.9 The Adaptive-Subspace SOM (ASSOM) -- 5.10 Feedback-Controlled Adaptive-Subspace SOM (FASSOM) -- 6. Learning Vector Quantization
-- 6.1 Optimal Decision -- 6.2 The LVQ1 -- 6.3 The Optimized-Learning-Rate LVQ1 (OLVQ1) -- 6.4 The LVQ2 (LVQ2.1) -- 6.5 The LVQ3 -- 6.6 Differences Between LVQ1, LVQ2 and LVQ3 -- 6.7 General Considerations -- 6.8 The Hypermap-Type LVQ
-- 6.9 The “LVQ-SOM” -- 7. Applications -- 7.1 Preprocessing of Optic Patterns -- 7.2 Acoustic Preprocessing -- 7.3 Process and Machine Monitoring -- 7.4 Diagnosis of Speech Voicing -- 7.5 Transcription of Continuous Speech -- 7.6
Texture Analysis -- 7.7 Contextual Maps -- 7.8 Organization of Large Document Files -- 7.9 Robot-Arm Control -- 7.10 Telecommunications -- 7.11 The SOM as an Estimator -- 8. Hardware for SOM -- 8.1 An Analog Classifier Circuit -- 8.2
Fast Digital Classifier Circuits -- 8.3 SIMD Implementation of SOM -- 8.4 Transputer Implementation of SOM -- 8.5 Systolic-Array Implementation of SOM -- 8.6 The COKOS Chip -- 8.7 The TInMANN Chip -- 9. An Overview of SOM Literature --
9.1 General -- 9.2 Early Works on Competitive Learning -- 9.3 Status of the Mathematical Analyses -- 9.4 Survey of General Aspects of the SOM -- 9.5 Modifications and Analyses of LVQ -- 9.6 Survey of Diverse Applications of SOM -- 9.7
Applications of LVQ -- 9.8 Survey of SOM and LVQ Implementations -- 9.9 New References in the Second Edition -- 10. Glossary of “Neural” Terms -- References
ISBN:9783642979668
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Springer Series in Information Sciences: 30
Keywords: Computer science , Neurosciences , Data mining , Artificial intelligence , Mathematics , Biophysics , Biological physics , Electrical engineering , Computer Science , Artificial Intelligence (incl. Robotics) , Data Mining and Knowledge Discovery , Neurosciences , Biophysics and Biological Physics , Communications Engineering, Networks , Mathematics, general
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