Advances in Intelligent Data Analysis

Table of Contents

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   Book Overview
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   Chapter 1 Feature Characterization in Scientific Datasets
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   Chapter 2 Relevance Feedback in the Bayesian Network Retrieval Model: An Approach Based on Term Instantiation
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   Chapter 3 Generating Fuzzy Summaries From Fuzzy Multidimensional Databases
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   Chapter 4 A Mixture-of-Experts Framework for Learning from Imbalanced Data Sets
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   Chapter 5 Predicting Time-Varying Functions with Local Models
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   Chapter 6 Building Models of Ecological Dynamics Using HMM Based Temporal Data Clustering — A Preliminary Study
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   Chapter 7 Tagging with Small Training Corpora
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   Chapter 8 A Search Engine for Morphologically Complex Languages
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    Chapter 9 Errors Detection and Correction in Large Scale Data Collecting
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    Chapter 10 A New Framework to Assess Association Rules
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    Chapter 11 Communities of Interest
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    Chapter 12 An Evaluation of Grading Classifiers
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    Chapter 13 Finding Informative Rules in Interval Sequences
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    Chapter 14 Correlation-Based and Contextual Merit-Based Ensemble Feature Selection
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    Chapter 15 Nonmetric Multidimensional Scaling with Neural Networks
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    Chapter 16 Functional Trees for Regression
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    Chapter 17 Data Mining with Products of Trees
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    Chapter 18 S3Bagging: Fast Classifier Induction Method with Subsampling and Bagging
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    Chapter 19 RNA-Sequence-Structure Properties and Selenocysteine Insertion
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    Chapter 20 An Algorithm for Segmenting Categorical Time Series into Meaningful Episodes
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    Chapter 21 An Empirical Comparison of Pruning Methods for Ensemble Classifiers
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    Chapter 22 A framework for Modelling Short, High-Dimensional Multivariate Time Series: Preliminary Results in Virus Gene Expression Data Analysis
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    Chapter 23 Using Multiattribute Prediction Suffix Graphs for Spanish Part-of-Speech Tagging
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    Chapter 24 Self-Supervised Chinese Word Segmentation
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    Chapter 25 Analyzing Data Clusters: A Rough Sets Approach to Extract Cluster-Defining Symbolic Rules
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    Chapter 26 Finding Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables
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    Chapter 27 Fluent Learning: Elucidating the Structure of Episodes
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    Chapter 28 An Intelligent Decision Support Model for Aviation Weather Forcasting
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    Chapter 29 MAMBO: Discovering Association Rules Based on Conditional Independencies
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    Chapter 30 Model Building for Random Fields
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    Chapter 31 Active Hidden Markov Models for Information Extraction
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    Chapter 32 Adaptive Lightweight Text Filtering
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    Chapter 33 General Algorithm for Approximate Inference in Multiply Sectioned Bayesian Networks
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    Chapter 34 Investigating Temporal Patterns of Fault Behaviour Within Large Telephony Networks
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    Chapter 35 Closed Set Based Discovery of Representative Association Rules
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    Chapter 36 Intelligent Sensor Analysis and Actuator Control
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    Chapter 37 Sampling of Highly Correlated Data for Polynomial Regression and Model Discovery
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    Chapter 38 The IDA’01 Robot Data Challenge