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Produktbild: Advances in Intelligent Data Analysis VII
Band 4723

Advances in Intelligent Data Analysis VII 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, Proceedings

Aus der Reihe Lecture Notes in Computer Science

49,99 €

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

28.08.2007

Herausgeber

Michael R. Berthold + weitere

Verlag

Springer Berlin

Seitenzahl

382

Maße (L/B/H)

24,2/15,7/2,7 cm

Gewicht

597 g

Auflage

2007

Sprache

Englisch

ISBN

978-3-540-74824-3

Beschreibung

Portrait

Prof. Dr. Nada Lavrac heads the Department of Knowledge Technologies at the Jo ef Stefan Institute in Ljubljana. She is the author and editor of several books and proceedings in the field of data mining and machine learning, and she has chaired or served on the boards of the main related journals and conferences. Her research interests include machine learning, data mining, and inductive logic programming, and related applications in medicine, public health, bioinformatics, and the management of virtual enterprises. In 1997 she was awarded the Ambassador of Science of Slovenia prize, and in 2007 she was elected as an ECCAI Fellow.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

28.08.2007

Herausgeber

Verlag

Springer Berlin

Seitenzahl

382

Maße (L/B/H)

24,2/15,7/2,7 cm

Gewicht

597 g

Auflage

2007

Sprache

Englisch

ISBN

978-3-540-74824-3

Herstelleradresse

Springer Nature Customer Service Center GmbH
Europaplatz 3
69115 Heidelberg
DE
ProductSafety@springernature.com

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  • Produktbild: Advances in Intelligent Data Analysis VII
  • Statistical Data Analysis.- Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions.- Multiplicative Updates for L 1–Regularized Linear and Logistic Regression.- Learning to Align: A Statistical Approach.- Transductive Reliability Estimation for Kernel Based Classifiers.- Bayesian Approaches.- Parameter Learning for Bayesian Networks with Strict Qualitative Influences.- Tree Augmented Naive Bayes for Regression Using Mixtures of Truncated Exponentials: Application to Higher Education Management.- Clustering Methods.- DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation.- Visualising the Cluster Structure of Data Streams.- Relational Topographic Maps.- Ensemble Learning.- Incremental Learning with Multiple Classifier Systems Using Correction Filters for Classification.- Combining Bagging and Random Subspaces to Create Better Ensembles.- Two Bagging Algorithms with Coupled Learners to Encourage Diversity.- Ranking.- Relational Algebra for Ranked Tables with Similarities: Properties and Implementation.- A New Way to Aggregate Preferences: Application to Eurovision Song Contests.- Trees.- Conditional Classification Trees Using Instrumental Variables.- Robust Tree-Based Incremental Imputation Method for Data Fusion.- Sequence/ Time Series Analysis.- Making Time: Pseudo Time-Series for the Temporal Analysis of Cross Section Data.- Recurrent Predictive Models for Sequence Segmentation.- Sequence Classification Using Statistical Pattern Recognition.- Knowledge Discovery.- Subrule Analysis and the Frequency-Confidence Diagram.- A Partial Correlation-Based Algorithm for Causal Structure Discovery with Continuous Variables.- Visualization.- Visualizing Sets of Partial Rankings.- A Partially Supervised Metric Multidimensional Scaling Algorithm for Textual Data Visualization.- Landscape Multidimensional Scaling.- Text Mining.- A Support Vector Machine Approach to Dutch Part-of-Speech Tagging.- Towards Adaptive Web Mining: Histograms and Contexts in Text Data Clustering.- Does SVM Really Scale Up to Large Bag of Words Feature Spaces?.- Bioinformatics.- Noise Filtering and Microarray Image Reconstruction Via Chained Fouriers.- Motif Discovery Using Multi-Objective Genetic Algorithm in Biosequences.- Soft Topographic Map for Clustering and Classification of Bacteria.- Applications.- Fuzzy Logic Based Gait Classification for Hemiplegic Patients.- Traffic Sign Recognition Using Discriminative Local Features.- Novelty Detection in Patient Histories: Experiments with Measures Based on Text Compression.