Sciweavers

23 search results - page 1 / 5
» Bagging and Boosting Negatively Correlated Neural Networks
Sort
View
TSMC
2008
164views more  TSMC 2008»
13 years 4 months ago
Bagging and Boosting Negatively Correlated Neural Networks
In this paper, we propose two cooperative ensemble learning algorithms, i.e., NegBagg and NegBoost, for designing neural network (NN) ensembles. The proposed algorithms incremental...
Md. Monirul Islam, Xin Yao, S. M. Shahriar Nirjon,...
IJCNN
2008
IEEE
13 years 11 months ago
On-line bagging Negative Correlation Learning
— Negative Correlation Learning (NCL) has been showing to outperform other ensemble learning approaches in off-line mode. A key point to the success of NCL is that the learning o...
Fernanda L. Minku, Xin Yao
ICANN
2003
Springer
13 years 10 months ago
A Comparison of Model Aggregation Methods for Regression
Combining machine learning models is a means of improving overall accuracy.Various algorithms have been proposed to create aggregate models from other models, and two popular examp...
Zafer Barutçuoglu
ICANN
2003
Springer
13 years 10 months ago
Neural Network Ensemble with Negatively Correlated Features for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it ex...
Hong-Hee Won, Sung-Bae Cho
ICANN
2009
Springer
13 years 8 months ago
Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning
This paper proposes a novel Mass Spectrometry data profiling method for ovarian cancer detection based on negative correlation learning (NCL). A modified Smoothed Nonlinear Energy ...
Shan He, Huanhuan Chen, Xiaoli Li, Xin Yao