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ML
2000
ACM
185views Machine Learning» more  ML 2000»
15 years 1 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
111
Voted
CP
2010
Springer
14 years 11 months ago
Ensemble Classification for Constraint Solver Configuration
The automatic tuning of the parameters of algorithms and automatic selection of algorithms has received a lot of attention recently. One possible approach is the use of machine lea...
Lars Kotthoff, Ian Miguel, Peter Nightingale
ICALT
2007
IEEE
15 years 3 months ago
An Ontological Approach for Semantic Learning Objects Interoperability
This paper presents a semantic-aware classification algorithm that can leverage the interoperability among semantically heterogeneous learning object repositories using different ...
Ming-Che Lee, Kun Hua Tsai, Tung Cheng Hsieh, Ti K...
MICCAI
2002
Springer
16 years 2 months ago
Comparative Exudate Classification Using Support Vector Machines and Neural Networks
After segmenting candidate exudates regions in colour retinal images we present and compare two methods for their classification. The Neural Network based approach performs margina...
Alireza Osareh, Majid Mirmehdi, Barry T. Thomas, R...
ICML
2010
IEEE
15 years 2 months ago
Boosting for Regression Transfer
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for...
David Pardoe, Peter Stone