Constructing Diverse Classifier Ensembles using Artificial Training Examples
By Prem Melville, Raymond J. Mooney. International Joint Conference on Artificial Intelligence, 2003
311 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/67049930a70b1ea731dc9a7a7e1646735d47e113
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Lior Rokach
- M. A. Ganaie
- Yoshua Bengio
- J. Urgen Schmidhuber
- Percy Liang
- R. Caruana
- Dacheng Tao
- Raymond J. Mooney
Citations in the corpus
- Ensemble-based classifiers (2010, methodology): “The DECORATE algorithm (Melville and Mooney 2003) is a dependent approach in which the ensemble is generated iteratively, learning a classifier at each iteration and adding it to the current ensemble.”
- Advances in Fuzzy Clustering and its Applications (2007, background): “where increasing the size of the ensemble increases the accuracy until a saturation point is reached (Hansen and Salamon 1990; Melville and Mooney 2003; Opitz and Maclin 1999).”
- Dual Strategy Active Learning (2007, unknown): “Our future plan is also to extend this work to ensemble methods that involve more than two strategies, maximizing ensemble diversity [15,14,10].”
- Model compression (2006, methodology): “DECORATE [13] uses artificial data to increase diversity so that better ensembles can be trained.”
- Ensemble deep learning: A review (2021, methodology): “In [154, 155], the author explores using an ensemble method that builds a diverse committee.”
- Diversity creation methods: a survey and categorisation (2004, methodology): “The DECORATE algorithm, by Melville and Mooney [ 49 ] utilises the same metric to decide whether to accept or reject predictors to be added to the ensemble.”
- Creating diversity in ensembles using artificial data (2005, background): “We present a new meta-learner Decorate (Diverse Ensemble Creation by Oppositional Relabeling of Artificial Training Examples) (Melville and Mooney, 2003), that uses an existing " strong " learner (one that provides high accuracy on the training data) to build an effective diverse committee in a…”
- Diverse ensembles for active learning (2004, methodology): “Decorate This section summarizes theDecorate algorithm; for further details see (Melville & Mooney, 2003; Melville & Mooney, 2004).”