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138
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ICML
2006
IEEE
16 years 4 months ago
An empirical comparison of supervised learning algorithms
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Rich Caruana, Alexandru Niculescu-Mizil
95
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ISJ
2002
71views more  ISJ 2002»
15 years 3 months ago
Educating reflective systems developers
Systems development research shows that practitioners seldom follow methods and that the competencies required for successful development of computer-based systems go well beyond t...
Lars Mathiassen, Sandeep Purao
270
Voted
ICANN
2011
Springer
14 years 7 months ago
Bias of Importance Measures for Multi-valued Attributes and Solutions
Attribute importance measures for supervised learning are important for improving both learning accuracy and interpretability. However, it is well-known there could be bias when th...
Houtao Deng, George C. Runger, Eugene Tuv
155
Voted
MLQ
2011
14 years 6 months ago
Coding into HOD via normal measures with some applications
We develop a new method for coding sets while preserving gch in the presence of large cardinals, particularly supercompact cardinals. We will use the number of normal measures carr...
Arthur W. Apter, Shoshana Friedman
129
Voted
ACL
2003
15 years 5 months ago
Text Chunking by Combining Hand-Crafted Rules and Memory-Based Learning
This paper proposes a hybrid of handcrafted rules and a machine learning method for chunking Korean. In the partially free word-order languages such as Korean and Japanese, a smal...
Seong-Bae Park, Byoung-Tak Zhang