E-raamat: Machine Learning and Data Mining in Pattern Recognition: 6th International Conference, MLDM 2009, Leipzig, Germany, July 23-25, 2009, Proceedings

Attribute Discretization and Data Preparation.- Improved
Comprehensibility and Reliability of Explanations via Restricted Halfspace
Discretization.- Selection of Subsets of Ordered Features in Machine
Learning.- Combination of Vector Quantization and Visualization.-
Discretization of Target Attributes for Subgroup Discovery.- Preserving
Privacy in Time Series Data Classification by Discretization.- Using
Resampling Techniques for Better Quality Discretization.- Classification.- A
Large Margin Classifier with Additional Features.- Sequential EM for
Unsupervised Adaptive Gaussian Mixture Model Based Classifier.- Optimal
Double-Kernel Combination for Classification.- Efficient AdaBoost Region
Classification.- A Linear Classification Method in a Very High Dimensional
Space Using Distributed Representation.- PMCRI: A Parallel Modular
Classification Rule Induction Framework.- Dynamic Score Combination: A
Supervised and Unsupervised Score Combination Method.- ODDboost:
Incorporating Posterior Estimates into AdaBoost.- Ensemble Classifier
Learning.- Ensemble Learning: A Study on Different Variants of the Dynamic
Selection Approach.- Relevance and Redundancy Analysis for Ensemble
Classifiers.- Drift-Aware Ensemble Regression.- Concept Drifting Detection on
Noisy Streaming Data in Random Ensemble Decision Trees.- Association Rules
and Pattern Mining.- Mining Multiple Level Non-redundant Association Rules
through Two-Fold Pruning of Redundancies.- Pattern Mining with Natural
Language Processing: An Exploratory Approach.- Is the Distance Compression
Effect Overstated? Some Theory and Experimentation.- Support Vector
Machines.- Fast Local Support Vector Machines for Large Datasets.- The Effect
of Domain Knowledge on Rule Extraction from Support Vector Machines.- Towards
B-Coloring of SOM.- Clustering.- CSBIterKmeans: A New Clustering Algorithm
Based on Quantitative Assessment of the Clustering Quality.- Agent-Based
Non-distributed and Distributed Clustering.- An Evidence Accumulation
Approach to Constrained Clustering Combination.- Fast Spectral Clustering
with Random Projection and Sampling.- How Much True Structure Has Been
Discovered?.- Efficient Clustering of Web-Derived Data Sets.- A Probabilistic
Approach for Constrained Clustering with Topological Map.- Novelty and
Outlier Detection.- Relational Frequent Patterns Mining for Novelty Detection
from Data Streams.- A Comparative Study of Outlier Detection Algorithms.-
Outlier Detection with Explanation Facility.- Learning.- Concept Learning
from (Very) Ambiguous Examples.- Finding Top-N Pseudo Formal Concepts with
Core Intents.- On Fixed Convex Combinations of No-Regret Learners.- An
Improved Tabu Search (ITS) Algorithm Based on Open Cover Theory for Global
Extremums.- The Needles-in-Haystack Problem.- Data Mining on Multimedia
Data.- An Evidence-Driven Probabilistic Inference Framework for Semantic
Image Understanding.- Detection of Masses in Mammographic Images Using
Simpsons Diversity Index in Circular Regions and SVM.- Mining Lung Shape
from X-Ray Images.- A Wavelet-Based Method for Detecting Seismic Anomalies in
Remote Sensing Satellite Data.- Spectrum Steganalysis of WAV Audio Streams.-
Audio-Based Emotion Recognition in Judicial Domain: A Multilayer Support
Vector Machines Approach.- Learning with a Quadruped Chopstick Robot.-
Dissimilarity Based Vector Space Embedding of Graphs Using Prototype
Reduction Schemes.- Text Mining.- Using Graph-Kernels to Represent Semantic
Information in Text Classification.- A General Framework of Feature Selection
for Text Categorization.- New SemanticSimilarity Based Model for Text
Clustering Using Extended Gloss Overlaps.- Aspects of Data Mining.- Learning
Betting Tips from Users Bet Selections.- An Approach to Web-Scale
Named-Entity Disambiguation.- A General Learning Method for Automatic
Title Extraction from HTML Pages.- Regional Pattern Discovery in
Geo-referenced Datasets Using PCA.- Memory-Based Modeling of Seasonality for
Prediction of Climatic Time Series.- A Neural Approach for SMEs Credit Risk
Analysis in Turkey.- Assisting Data Mining through Automated Planning.-
Predictions with Confidence in Applications.- Data Mining in Medicine.-
Aligning Bayesian Network Classifiers with Medical Contexts.- Assessing the
Eligibility of Kidney Transplant Donors.- Lung Nodules Classification in CT
Images Using Simpsons Index, Geometrical Measures and One-Class SVM.