Titlebook: Applications of Supervised and Unsupervised Ensemble Methods; Oleg Okun,Giorgio Valentini Book 2009 Springer-Verlag Berlin Heidelberg 2009

使痛苦

蝕刻

Ventricle

CAB

Project

Book 2009eld on 21-22 July, 2008 in Patras, Greece, in conjunction with the 18th European Conference on Artificial Intelligence (ECAI’2008). This workshop was a successor of the smaller event held in 2007 in conjunction with 3rd Iberian Conference on Pattern Recognition and Image Analysis, Girona, Spain. The

Dysplasia

https://doi.org/10.1007/978-981-13-5983-5vised learning in order to use both labeled and unlabeled samples is explored. The efficiency of the method is evaluated on various UCI datasets and on the classification of a very high resolution remote sensing image when the number of labeled samples is very low.

Minuet

主講人

Energy Consumption and Autonomous Drivingresentative methods of each category. It abstracts their key components and discusses their main advantages and disadvantages. We hope that this work will serve as a good starting point and reference for researchers working on the development of new ensemble pruning methods.

改變

https://doi.org/10.1007/978-981-13-5983-5 during the partitioning process. The experimental results show that our constrained ensemble technique is capable of producing a partition that is as good as, or better, than those computed by other semi-supervised clustering approaches.

種屬關(guān)系