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» Evaluating learning algorithms and classifiers
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CSL
2008
Springer
15 years 6 months ago
An Optimal Strategy Improvement Algorithm for Solving Parity and Payoff Games
This paper presents a novel strategy improvement algorithm for parity and payoff games, which is guaranteed to select, in each improvement step, an optimal combination of local str...
Sven Schewe
SDM
2008
SIAM
165views Data Mining» more  SDM 2008»
15 years 5 months ago
On the Dangers of Cross-Validation. An Experimental Evaluation
Cross validation allows models to be tested using the full training set by means of repeated resampling; thus, maximizing the total number of points used for testing and potential...
R. Bharat Rao, Glenn Fung
IJSI
2008
156views more  IJSI 2008»
15 years 4 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
MOBISYS
2010
ACM
15 years 6 months ago
Darwin phones: the evolution of sensing and inference on mobile phones
We present Darwin, an enabling technology for mobile phone sensing that combines collaborative sensing and classification techniques to reason about human behavior and context on ...
Emiliano Miluzzo, Cory Cornelius, Ashwin Ramaswamy...
ICML
2003
IEEE
15 years 9 months ago
An Evaluation on Feature Selection for Text Clustering
Feature selection methods have been successfully applied to text categorization but seldom applied to text clustering due to the unavailability of class label information. In this...
Tao Liu, Shengping Liu, Zheng Chen, Wei-Ying Ma