Combination of Task Description Strategies and Case Base Properties for Meta-Learning
By Christian Rudolf Köpf, Ioannis Iglezakis. 2002
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Radwa El Shawi
- Marcin Budka
- Mohamed Maher
- Christiane Lemke
- Sherif Sakr
- Bogdan Gabrys
- Marc-André Zöller
- Mirko Kück
Citations in the corpus
- Automated Machine Learning: State-of-The-Art and Open Challenges (2019, background): “There exists a rich literature on using meta models for model configuration recommendations [114, 92, 65, 68, 44].”
- Meta-Learning: A Survey (2018, neutral): “Experiments showed that boosted and bagged trees often yielded the best predictions, although much depends on the exact meta-features used [72, 76].”
- Metalearning: a survey of trends and technologies (2013, methodology): “In a similar approach, Köpf and Iglezakis (2002) also suggest comparing observations with each other and extract ‘case base properties’, which assess the quality of a dataset using measures such as redundancy, for example induced by data records that are exactly the same, or incoherency, which, for…”