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» Selection of Decision Stumps in Bagging Ensembles
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IDA
2007
Springer
13 years 11 months ago
Combining Bagging and Random Subspaces to Create Better Ensembles
Random forests are one of the best performing methods for constructing ensembles. They derive their strength from two aspects: using random subsamples of the training data (as in b...
Pance Panov, Saso Dzeroski
BMCBI
2008
219views more  BMCBI 2008»
13 years 5 months ago
Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles
Background: Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detect...
Guangtao Ge, G. William Wong
AIPRF
2007
13 years 7 months ago
Evaluation of Different Approaches to Training a Genre Classifier
This paper presents experiments on classifying web pages by genre. Firstly, a corpus of 1539 manually labeled web pages was prepared. Secondly, 502 genre features were selected ba...
Vedrana Vidulin, Mitja Lustrek, Matjaz Gams
CSL
2006
Springer
13 years 5 months ago
A study in machine learning from imbalanced data for sentence boundary detection in speech
Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have const...
Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizab...
AUSDM
2006
Springer
202views Data Mining» more  AUSDM 2006»
13 years 9 months ago
A Comparative Study of Classification Methods For Microarray Data Analysis
In response to the rapid development of DNA Microarray technology, many classification methods have been used for Microarray classification. SVMs, decision trees, Bagging, Boostin...
Hong Hu, Jiuyong Li, Ashley W. Plank, Hua Wang, Gr...