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» Learning with Mixtures of Trees
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KDD
2009
ACM
196views Data Mining» more  KDD 2009»
14 years 2 months ago
WhereNext: a location predictor on trajectory pattern mining
The pervasiveness of mobile devices and location based services is leading to an increasing volume of mobility data. This side effect provides the opportunity for innovative meth...
Anna Monreale, Fabio Pinelli, Roberto Trasarti, Fo...
ML
2000
ACM
185views Machine Learning» more  ML 2000»
13 years 7 months ago
A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms
Twenty-two decision tree, nine statistical, and two neural network algorithms are compared on thirty-two datasets in terms of classification accuracy, training time, and (in the ca...
Tjen-Sien Lim, Wei-Yin Loh, Yu-Shan Shih
ENGL
2007
148views more  ENGL 2007»
13 years 8 months ago
A General Reflex Fuzzy Min-Max Neural Network
—“A General Reflex Fuzzy Min-Max Neural Network” (GRFMN) is presented. GRFMN is capable to extract the underlying structure of the data by means of supervised, unsupervised a...
Abhijeet V. Nandedkar, Prabir Kumar Biswas
BMCBI
2010
110views more  BMCBI 2010»
13 years 8 months ago
Discovering local patterns of co - evolution: computational aspects and biological examples
Background: Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn abo...
Tamir Tuller, Yifat Felder, Martin Kupiec
TSMC
2008
100views more  TSMC 2008»
13 years 8 months ago
Instruction-Matrix-Based Genetic Programming
In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In th...
Gang Li, Jin Feng Wang, Kin-Hong Lee, Kwong-Sak Le...