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» On Feature Selection, Bias-Variance, and Bagging
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BMCBI
2010
224views more  BMCBI 2010»
13 years 5 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
PR
2011
12 years 7 months ago
Hierarchical annotation of medical images
In this paper, we describe an approach for the automatic medical annotation task of the 2008 CLEF cross-language image retrieval campaign (ImageCLEF). The data comprise 12076 full...
Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, ...
CIARP
2006
Springer
13 years 8 months ago
Oscillating Feature Subset Search Algorithm for Text Categorization
Abstract. A major characteristic of text document categorization problems is the extremely high dimensionality of text data. In this paper we explore the usability of the Oscillati...
Jana Novovicová, Petr Somol, Pavel Pudil
ESANN
2006
13 years 6 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
EMNLP
2008
13 years 6 months ago
Selecting Sentences for Answering Complex Questions
Complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topicoriented, informative multi-document summarization. I...
Yllias Chali, Shafiq R. Joty