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» New Insights into Learning Algorithms and Datasets
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ICMLA
2008
13 years 5 months ago
New Insights into Learning Algorithms and Datasets
We report on three distinct experiments that provide new valuable insights into learning algorithms and datasets. We first describe two effective meta-features that significantly ...
Jun Won Lee, Christophe G. Giraud-Carrier
MCS
2010
Springer
13 years 9 months ago
Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC
We have previously described an incremental learning algorithm, Learn++ .NC, for learning from new datasets that may include new concept classes without accessing previously seen d...
Gregory Ditzler, Michael D. Muhlbaier, Robi Polika...
JMLR
2012
11 years 6 months ago
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
Alexandre Lacoste, François Laviolette, Mar...
CANDC
2009
ACM
13 years 10 months ago
A sub-symbolic model of the cognitive processes of re-representation and insight
We present a sub-symbolic computational model for effecting knowledge re-representation and insight. Given a set of data, manifold learning is used to automatically organize the d...
Dan Ventura
AUSAI
2008
Springer
13 years 6 months ago
Clustering with XCS on Complex Structure Dataset
Learning Classifier System (LCS) is an effective tool to solve classification problems. Clustering with XCS (accuracy-based LCS) is a novel approach proposed recently. In this pape...
Liangdong Shi, Yang Gao, Lei Wu, Lin Shang