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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

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2013
Highly Cited
2013
Learning Markov Networks With Arithmetic Circuits
Markov networks are an effective way to represent complex probability distributions. However, learning their structure and… 
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… 
2012
2012
Estimating size fraction categories of coal particles on conveyor belts using image texture modeling methods
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… 
2006
2006
Detecting Noisy Instances with the Ensemble Filter: a Study in Software Quality Estimation
The performance of a classification model is invariably affected by the characteristics of the measurement data it is built upon… 
Highly Cited
2005
Highly Cited
2005
Support Vector Inductive Logic Programming
In this paper we explore a topic which is at the intersection of two areas of Machine Learning: namely Support Vector Machines… 
1996
1996
Cloud Classiication Using Error-correcting Output Codes
Novel arti cial intelligence methods are used to classify 16x16 pixel regions (obtained from Advanced Very High Resolution… 
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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