Measures for combining accuracy and time for meta-learning

CEUR Workshop Proceedings

Volumn 1201, Issue , 2014, Pages 49-50

  Abdulrahman, Salisu Mamman ^a   Brazdil, Pavel ^a  

^a UNIVERSITY OF PORTO   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE;

METALEARNING; MODEL-BASED OPC; MONOTONICITY; PERFORMANCE MEASURE; TRAINING TIME;

LEARNING ALGORITHMS;

EID: 84908262592     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. P. Brazdil, C. Giraud-Carrier, C. Soares, and R. Vilalta, Metalearning: Applications to Data Mining, Springer, 2009.
2. Kalousis, A. (2002). Algorithm selection via meta-learning. PhD Thesis. University of Geneva.
3. Gama, J. and P. Brazdil (1995). Characterization of classification algorithms. Lecture Notes in Computer Science 990, 189-200.
4. Brazdil, P. B, C. Soares, and Joaquin Pinto Da Costa. "Ranking learning algorithms: Using IBL and meta-learning on accuracy and time results." Machine Learning 50.3 (2003): 251-277.
5. Leite, R, and P. Brazdil. "Active Testing Strategy to Predict the Best Classification Algorithm via Sampling and Metalearning." ECAI. 2010.
6. Vanschoren, J. "The experiment database for machine learning." 5th Planning to Learn Workshop, WS28 at ECAI-2012. 2012.