Integrating Multiple Learning Strategies in First Order Logics
Machine Learning - Special issue on multistrategy learning
A Survey of Methods for Scaling Up Inductive Algorithms
Data Mining and Knowledge Discovery
A perspective view and survey of meta-learning
Artificial Intelligence Review
Machine Learning and Its Applications, Advanced Lectures
Improved Dataset Characterisation for Meta-learning
DS '02 Proceedings of the 5th International Conference on Discovery Science
Integrating Declarative Knowledge in Hierarchical Clustering Tasks
IDA '99 Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis
Handbook of data mining and knowledge discovery
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Introduction to the Special Issue on Meta-Learning
Machine Learning
IEEE Transactions on Knowledge and Data Engineering
How to shift bias: Lessons from the baldwin effect
Evolutionary Computation
Mindful: A framework for Meta-INDuctive neuro-FUzzy Learning
Information Sciences: an International Journal
Meta-learning optimal parameter values in non-stationary environments
Knowledge-Based Systems
Journal of Artificial Intelligence Research
MMDT: a multi-valued and multi-labeled decision tree classifier for data mining
Expert Systems with Applications: An International Journal
Evaluating learning algorithms and classifiers
International Journal of Intelligent Information and Database Systems
The Knowledge Engineering Review
Evolution-based discovery of hierarchical behaviors
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Distributed learning with data reduction
Transactions on computational collective intelligence IV
Artificial Intelligence in Medicine
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In this introduction, we define the term bias as it is used in machine learning systems. We motivate the importance of automated methods for evaluating and selecting biases using a framework of bias selection as search in bias and meta-bias spaces. Recent research in the field of machine learning bias is summarized.