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Machine Learning and Data Mining in Pattern Recognition

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Cover of 'Machine Learning and Data Mining in Pattern Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Introspective Learning to Build Case-Based Reasoning (CBR) Knowledge Containers
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    Chapter 2 Graph-Based Tools for Data Mining and Machine Learning
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    Chapter 3 Simplification Methods for Model Trees with Regression and Splitting Nodes
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    Chapter 4 Learning Multi-label Alternating Decision Trees from Texts and Data
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    Chapter 5 Khiops: A Discretization Method of Continuous Attributes with Guaranteed Resistance to Noise
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    Chapter 6 On the Size of a Classification Tree
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    Chapter 7 A Comparative Analysis of Clustering Algorithms Applied to Load Profiling
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    Chapter 8 Similarity-Based Clustering of Sequences Using Hidden Markov Models
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    Chapter 9 A Fast Parallel Optimization for Training Support Vector Machine
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    Chapter 10 A ROC-Based Reject Rule for Support Vector Machines
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    Chapter 11 Remembering Similitude Terms in CBR
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    Chapter 12 Authoring Cases from Free-Text Maintenance Data
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    Chapter 13 Classification Boundary Approximation by Using Combination of Training Steps for Real-Time Image Segmentation
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    Chapter 14 Simple Mimetic Classifiers
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    Chapter 15 Novel Mixtures Based on the Dirichlet Distribution: Application to Data and Image Classification
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    Chapter 16 Estimating a Quality of Decision Function by Empirical Risk
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    Chapter 17 Efficient Locally Linear Embeddings of Imperfect Manifolds
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    Chapter 18 Dissimilarity Representation of Images for Relevance Feedback in Content-Based Image Retrieval
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    Chapter 19 A Rule-Based Scheme for Filtering Examples from Majority Class in an Imbalanced Training Set
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    Chapter 20 Coevolutionary Feature Learning for Object Recognition
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    Chapter 21 Generalization of Pattern-Growth Methods for Sequential Pattern Mining with Gap Constraints
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    Chapter 22 Discover Motifs in Multi-dimensional Time-Series Using the Principal Component Analysis and the MDL Principle
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    Chapter 23 Optimizing Financial Portfolios from the Perspective of Mining Temporal Structures of Stock Returns
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    Chapter 24 Visualizing Sequences of Texts Using Collocational Networks
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    Chapter 25 Complexity Analysis of Depth First and FP-Growth Implementations of APRIORI
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    Chapter 26 GO-SPADE: Mining Sequential Patterns over Datasets with Consecutive Repetitions
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    Chapter 27 Using Test Plans for Bayesian Modeling
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    Chapter 28 Using Bayesian Networks to Analyze Medical Data
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    Chapter 29 A Belief Networks-Based Generative Model for Structured Documents. An Application to the XML Categorization
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    Chapter 30 Neural Self-Organization Using Graphs
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    Chapter 31 Integrating Fuzziness with OLAP Association Rules Mining
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    Chapter 32 Discovering Association Patterns Based on Mutual Information
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    Chapter 33 Connectionist Probability Estimators in HMM Arabic Speech Recognition Using Fuzzy Logic
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    Chapter 34 Shape Recovery from an Unorganized Image Sequence
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    Chapter 35 A Learning Autonomous Driver System on the Basis of Image Classification and Evolutional Learning
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    Chapter 36 Detecting the Boundary Curve of Planar Random Point Set
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    Chapter 37 A Machine Learning Model for Information Retrieval with Structured Documents
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Mentioned by

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Citations

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Readers on

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553 Mendeley
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Title
Machine Learning and Data Mining in Pattern Recognition
Published by
Springer, Berlin, Heidelberg, January 2003
DOI 10.1007/3-540-45065-3
ISBNs
978-3-54-040504-7, 978-3-54-045065-8
Editors

Petra Perner, Azriel Rosenfeld

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 553 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 1%
Germany 5 <1%
Brazil 4 <1%
India 4 <1%
Colombia 3 <1%
France 2 <1%
Russia 2 <1%
Japan 2 <1%
Portugal 2 <1%
Other 8 1%
Unknown 514 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 122 22%
Student > Master 122 22%
Student > Bachelor 68 12%
Researcher 62 11%
Student > Doctoral Student 23 4%
Other 68 12%
Unknown 88 16%
Readers by discipline Count As %
Computer Science 221 40%
Engineering 96 17%
Agricultural and Biological Sciences 21 4%
Business, Management and Accounting 16 3%
Environmental Science 10 2%
Other 89 16%
Unknown 100 18%