Machine Learning: ECML 2004

Language: English

Published by Springer, Springer Sep 2004, 2004

3540231056 / 9783540231059

  • Softcover
  • New
See all details

Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000

5-star seller

AbeBooks seller since January 23, 2017

View this seller's items
Softcover

Condition: New

US$ 63.28

US$ 68.92 shipping 
Ships from Germany to U.S.A.

Quantity: 1 available

Add to basket
Free 30-day returns

Item description from seller

This item is printed on demand - Print on Demand Titel. Neuware -Invited Papers.- Random Matrices in Data Analysis.- Data Privacy.- Breaking Through the Syntax Barrier: Searching with Entities and Relations.- Real-World Learning with Markov Logic Networks.- Strength in Diversity: The Advance of Data Analysis.- Contributed Papers.- Filtered Reinforcement Learning.- Applying Support Vector Machines to Imbalanced Datasets.- Sensitivity Analysis of the Result in Binary Decision Trees.- A Boosting Approach to Multiple Instance Learning.- An Experimental Study of Different Approaches to Reinforcement Learning in Common Interest Stochastic Games.- Learning from Message Pairs for Automatic Email Answering.- Concept Formation in Expressive Description Logics.- Multi-level Boundary Classification for Information Extraction.- An Analysis of Stopping and Filtering Criteria for Rule Learning.- Adaptive Online Time Allocation to Search Algorithms.- Model Approximation for HEXQ Hierarchical Reinforcement Learning.- Iterative Ensemble Classification for RelationalData: A Case Study of Semantic Web Services.- Analyzing Multi-agent Reinforcement Learning Using Evolutionary Dynamics.- Experiments in Value Function Approximation with Sparse Support Vector Regression.- Constructive Induction for Classifying Time Series.- Fisher Kernels for Logical Sequences.- The Enron Corpus: A New Dataset for Email Classification Research.- Margin Maximizing Discriminant Analysis.- Multi-objective Classification with Info-Fuzzy Networks.- Improving Progressive Sampling via Meta-learning on Learning Curves.- Methods for Rule Conflict Resolution.- An Efficient Method to Estimate Labelled Sample Size for Transductive LDA(QDA/MDA) Based on Bayes Risk.- Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection.- Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework.- Justification-Based Selection of Training Examples for Case Base Reduction.- Using Feature Conjunctions Across Examples for Learning Pairwise Classifiers.- Feature Selection Filters Based on the Permutation Test.- Sparse Distributed Memories for On-Line Value-Based Reinforcement Learning.- Improving Random Forests.- The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering.- Using String Kernels to Identify Famous Performers from Their Playing Style.- Associative Clustering.- Learning to Fly Simple and Robust.- Bayesian Network Methods for Traffic Flow Forecasting with Incomplete Data.- Matching Model Versus Single Model: A Study of the Requirement to Match Class Distribution Using Decision Trees.- Inducing Polynomial Equations for Regression.- Efficient Hyperkernel Learning Using Second-Order Cone Programming.- Effective Voting of Heterogeneous Classifiers.- Convergence and Divergence in Standard and Averaging Reinforcement Learning.- Document Representation for One-Class SVM.- Naive Bayesian Classifiers for Ranking.- Conditional Independence Trees.- Exploiting Unlabeled Data in Content-BasedImage Retrieval.- Population Diversity in Permutation-Based Genetic Algorithm.- Simultaneous Concept Learning of Fuzzy Rules.- Posters.- SWITCH: A Novel Approach to Ensemble Learning for Heterogeneous Data.- Estimating Attributed Central Orders.- Batch Reinforcement Learning with State Importance.- Explicit Local Models: Towards 'Optimal' Optimization Algorithms.- An Intelligent Model for the Signorini Contact Problem in Belt Grinding Processes.- Cluster-Grouping: From Subgroup Discovery to Clustering.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 600 pp. Englisch.

Seller Inventory # 9783540231059

Title
Machine Learning: ECML 2004
Author
Jean-Francois Boulicaut
Publisher
Springer, Springer Sep 2004
Publication year
2004
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3540231056
ISBN 13
9783540231059
Item weight
896 grams
Dimensions
235x155x33 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

5-star seller

AbeBooks seller since January 23, 2017

Shipping rates from Germany to U.S.A.

Item60 to 60 business days60 to 60 business days
First itemUS$ 68.92US$ 86.15
Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.

Payment methods

  • Visa
  • Mastercard
  • American Express
  • Apple Pay
  • Google Pay
  • Check
  • Paypal

Store description

Impressum Thorsten Retsch Buchversand Mimpf2000 Oberölschnitz 16 95517 Emtmannsberg Deutschland Telefon: 09209-2023188 Email: mimpf2000@online.de USt-ID-Nr.: DE 235096871 Wir führen gebrauchte Bücher aus allen Sparten der Literatur

Specialty

Modernes Antiquariat - Bücher von 1960 bis heute

Seller's business information

buchversandmimpf2000

Germany