Sciweavers

154 search results - page 13 / 31
» Boosted Bayesian network classifiers
Sort
View
MCS
2000
Springer
15 years 1 months ago
Ensemble Methods in Machine Learning
Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a (weighted) vote of their predictions. The original ensembl...
Thomas G. Dietterich
ARTMED
2004
133views more  ARTMED 2004»
14 years 9 months ago
Bayesian network multi-classifiers for protein secondary structure prediction
Successful secondary structure predictions provide a starting point for direct tertiary structure modelling, and also can significantly improve sequence analysis and sequence-stru...
Víctor Robles, Pedro Larrañaga, Jos&...
86
Voted
ECSQARU
2009
Springer
14 years 7 months ago
When in Doubt ... Be Indecisive
For a presented case, a Bayesian network classifier in essence computes a posterior probability distribution over its class variable. Based upon this distribution, the classifier&#...
Linda C. van der Gaag, Silja Renooij, Wilma Steene...
ICANN
2007
Springer
15 years 3 months ago
Boosting Unsupervised Competitive Learning Ensembles
Topology preserving mappings are great tools for data visualization and inspection in large datasets. This research presents a combination of several topology preserving mapping mo...
Emilio Corchado, Bruno Baruque, Hujun Yin
JIPS
2007
92views more  JIPS 2007»
14 years 9 months ago
Optimization of Domain-Independent Classification Framework for Mood Classification
In this paper, we introduce a domain-independent classification framework based on both k-nearest neighbor and Naïve Bayesian classification algorithms. The architecture of our s...
Sung-Pil Choi, Yuchul Jung, Sung-Hyon Myaeng