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ICML
2001
IEEE
16 years 5 months ago
Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection
In this paper, we examine the advantages and disadvantages of filter and wrapper methods for feature selection and propose a new hybrid algorithm that uses boosting and incorporat...
Sanmay Das
ICML
2006
IEEE
16 years 5 months ago
Feature subset selection bias for classification learning
Feature selection is often applied to highdimensional data prior to classification learning. Using the same training dataset in both selection and learning can result in socalled ...
Surendra K. Singhi, Huan Liu
SETN
2010
Springer
15 years 11 months ago
Feature Selection for Improved Phone Duration Modeling of Greek Emotional Speech
In the present work we address the problem of phone duration modeling for the needs of emotional speech synthesis. Specifically, relying on ten well known machine learning techniqu...
Alexandros Lazaridis, Todor Ganchev, Iosif Mporas,...
ICASSP
2008
IEEE
15 years 10 months ago
Discriminative feature selection for hidden Markov models using Segmental Boosting
We address the feature selection problem for hidden Markov models (HMMs) in sequence classification. Temporal correlation in sequences often causes difficulty in applying featur...
Pei Yin, Irfan A. Essa, Thad Starner, James M. Reh...
CIKM
2008
Springer
15 years 6 months ago
Structure feature selection for graph classification
With the development of highly efficient graph data collection technology in many application fields, classification of graph data emerges as an important topic in the data mining...
Hongliang Fei, Jun Huan