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Lazy learning

Known as: Lazy-learning 
In machine learning, lazy learning is a learning method in which generalization beyond the training data is delayed until a query is made to the… Expand
Wikipedia

Related topics

Related topics

6 relations
Eager learningGaussian processInstance-based learningK-nearest neighbors algorithm
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Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2010
2010
Completely Lazy Learning
Local classifiers are sometimes called lazy learners because they do not train a classifier until presented with a test sample… Expand
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Highly Cited
2008
Highly Cited
2008
An Empirical Study of Lazy Multilabel Classification Algorithms
Multilabel classification is a rapidly developing field of machine learning. Despite its short life, various methods for solving… Expand
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Highly Cited
2008
Highly Cited
2008
A Lazy Approach to Associative Classification
Associative classification is a promising technique to build accurate classifiers. However, in large or correlated data sets… Expand
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Highly Cited
2007
Highly Cited
2007
ML-KNN: A lazy learning approach to multi-label learning
Multi-label learning originated from the investigation of text categorization problem, where each document may belong to several… Expand
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Highly Cited
2004
Highly Cited
2004
The Racing Algorithm: Model Selection for Lazy Learners
Given a set of models and some training data, we would like to find the model that best describes the data. Finding the model… Expand
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Highly Cited
2004
Highly Cited
2004
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence… Expand
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Highly Cited
2000
Highly Cited
2000
Solving the Multiple-Instance Problem: A Lazy Learning Approach
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances… Expand
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1997
1997
Lazy Learning for Local Modeling and Control
  • DesignGianluca Bontempi, Mauro Birattari, Hugues BersiniIridia
  • 1997
    • Corpus ID: 15638829
This paper presents local methods for modeling and control of discrete-time unknown nonlinear dynamical systems, when only a… Expand
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Review
1997
Review
1997
A Review and Empirical Evaluation of Feature Weighting Methods for a Class of Lazy Learning Algorithms
Many lazy learning algorithms are derivatives of the k-nearest neighbor (k-NN) classifier, which uses a distance function to… Expand
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Highly Cited
1996
Highly Cited
1996
Lazy Decision Trees
Lazy learning algorithms, exemplified by nearest-neighbor algorithms, do not induce a concise hypothesis from a given training… Expand
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