Titlebook: Machine Learning: ECML 2007; 18th European Confer Joost N. Kok,Jacek Koronacki,Andrzej Skowron Conference proceedings 2007 Springer-Verlag

FERN

书目名称Machine Learning: ECML 2007影响因子(影响力)




书目名称Machine Learning: ECML 2007影响因子(影响力)学科排名




书目名称Machine Learning: ECML 2007网络公开度




书目名称Machine Learning: ECML 2007网络公开度学科排名




书目名称Machine Learning: ECML 2007被引频次




书目名称Machine Learning: ECML 2007被引频次学科排名




书目名称Machine Learning: ECML 2007年度引用




书目名称Machine Learning: ECML 2007年度引用学科排名




书目名称Machine Learning: ECML 2007读者反馈




书目名称Machine Learning: ECML 2007读者反馈学科排名

Headstrong

Neighborhood-Based Local Sensitivitycal sensitivity. The resulting estimates demonstrate improved performance when used in classifier combination and classifier recalibration as well as being potentially useful in active learning and a variety of other problems.

最有利

bronchodilator

Level Learning Set: A Novel Classifier Based on Active Contour Modelss in its ability to directly construct complex decision boundaries, and in better knowledge representation. Various experimental results including comparisons to existing machine learning algorithms are presented, and the advantages of the proposed approach are discussed.

配偶

Learning Partially Observable Markov Models from First Passage Timesransitions with the lowest expected passage times are trimmed off from the model. Practical evaluations on artificially generated data and on DNA sequence modeling show the benefits over Bayesian model induction or EM estimation of ergodic models with transition trimming.

output

Demonstrate

推延

Oafishness

CORD

Constraint Selection by Committee: An Ensemble Approach to Identifying Informative Constraints for Srmative, if known. An evaluation on text data shows that this provides an effective criterion for identifying constraints, leading to a reduction in the level of supervision required to direct a clustering algorithm to an accurate solution.