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Inductive bias

Known as: Learning bias 
The inductive bias (also known as learning bias) of a learning algorithm is the set of assumptions that the learner uses to predict outputs given… 
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Related topics

Related topics

11 relations
Cross-validation (statistics)Feature selectionK-nearest neighbors algorithmMeta learning (computer science)

Broader (1)

Machine learning

Papers overview

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2013
2013
Bayesian Discovery of Multiple Bayesian Networks via Transfer Learning
  • D. OyenT. Lane
  • IEEE 13th International Conference on Data Mining
  • 2013
  • Corpus ID: 10240609
Bayesian network structure learning algorithms with limited data are being used in domains such as systems biology and… 
2007
2007
Can Sustainable Consumption Be Learned
This paper shows how sustainable consumption patterns can spread within a population via processes of social learning even though… 
2007
2007
In Search Of Articulated Attractors
Recurrent attractor networks offer many advantages over feedforward networks for the modeling of psychological phenomena. Their… 
2007
2007
A general framework for imprecise regression
Many studies on machine learning, and more specifically on regression, focus on the search for a precise model, when precise data… 
2007
2007
Applying Case Based Based Reasoning to Sensor Fusion
One of the possible causes for global warming is the human intervention in the environment. The increasing amount of industrial… 
2005
2005
Infant-directed speech and the evolution of language
0.1 Introduction Language is an extremely complex phenomenon and evolutionary accounts of it are therefore often considered… 
2003
2003
Learning Biases for the Evolution of Linguistic Structure: An Associative Network Model
Structural hallmarks of language can be explained in terms of adaptation, by language, to pressures arising during its cultural… 
1999
1999
Learning to deal with risk: what does reinforcement learning tell us about risk atittudes?
People are generally reluctant to accept risk. In particular, people overvalue sure gains, relative to outcomes which are merely… 
1998
1998
On the development of inductive learning algorithms: generating flexible and adaptable concept representations
Vast amount of research in machine learning has focused on creating new algorithms stemming from reenements to existing learning… 
1989
1989
Integration of generic learning tasks
This paper presents a novel approach for the creation of intelligent machine learning programs. It introduces generic learning… 
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