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SDM
2004
SIAM
187views Data Mining» more  SDM 2004»
14 years 10 months ago
Class-Specific Ensembles for Active Learning
In many real-world tasks of image classification, limited amounts of labeled data are available to train automatic classifiers. Consequently, extensive human expert involvement is...
Amit Mandvikar, Huan Liu
ICMCS
2006
IEEE
173views Multimedia» more  ICMCS 2006»
15 years 3 months ago
Applying Supervised Classifiers Based on Non-negative Matrix Factorization to Musical Instrument Classification
In this paper, a new approach for automatic audio classification using non-negative matrix factorization (NMF) is presented. Training is performed onto each audio class individua...
Emmanouil Benetos, Margarita Kotti, Constantine Ko...
CSB
2004
IEEE
146views Bioinformatics» more  CSB 2004»
15 years 1 months ago
Automated Protein Classification Using Consensus Decision
We propose a novel technique for automatically generating the SCOP classification of a protein structure with high accuracy. High accuracy is achieved by combining the decisions o...
Tolga Can, Orhan Çamoglu, Ambuj K. Singh, Y...
CISSE
2008
Springer
14 years 11 months ago
Sentiment Mining Using Ensemble Classification Models
We live in the information age, where the amount of data readily available already overwhelms our capacity to analyze and absorb it without help from our machines. In particular, ...
Matthew Whitehead, Larry Yaeger
BMCBI
2010
150views more  BMCBI 2010»
14 years 9 months ago
Automatic structure classification of small proteins using random forest
Background: Random forest, an ensemble based supervised machine learning algorithm, is used to predict the SCOP structural classification for a target structure, based on the simi...
Pooja Jain, Jonathan D. Hirst