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Supervised learning

Known as: Fully-supervised machine learning, Supervised Machine Learning, Supervised classification 
Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training… 
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Related topics

Related topics

49 relations
Anomaly detectionBackpropagationBias–variance tradeoffBioinformatics

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2009
Highly Cited
2009
Object-oriented texture analysis for the unsupervised segmentation of biopsy images for cancer detection
Highly Cited
2009
Highly Cited
2009
Analytical Features: A Knowledge-Based Approach to Audio Feature Generation
We present a feature generation system designed to create audio features for supervised classification tasks. The main… 
Highly Cited
2007
Highly Cited
2007
Graph Embedding and Extensions
Over the past few decades, a large family of algorithms—supervised or unsupervised; stemming from statistics or geometry theory… 
Highly Cited
2006
Highly Cited
2006
Hand Image Segmentation in Video Sequence by GMM: a comparative analysis
This paper describes different approaches of realtime GMM (Gaussian mixture method) background subtraction algorithm using video… 
Highly Cited
2004
Highly Cited
2004
SenseLearner: Minimally supervised Word Sense Disambiguation for all words in open text
This paper introduces SenseLearner - a minimally supervised sense tagger that attempts to disambiguate all content words in a… 
Highly Cited
2003
Highly Cited
2003
Quasi Maximum Likelihood Blind Deconvolution of Images Using Optimal Sparse Representations
A quasi maximum likelihood framework for blind deconvolution of images is presented. We generalize the relative Newton algorithm… 
Highly Cited
2001
Highly Cited
2001
Learning with labeled and unlabeled dataMatthias
Highly Cited
1996
Highly Cited
1996
Mapping Ecological Land Systems and Classification Uncertainties from Digital Elevation and Forest-Cover Data Using Neural Networks
Our approaches in this project emphasized mainly the technical aspects of the land-systems classification problem with neural… 
Review
1996
Review
1996
Drug Use in the Nursing Home
With increasing pressure on hospitals to shorten acute-care stays, and the unprecedented aging of the population in… 
Highly Cited
1991
Highly Cited
1991
Tool condition monitoring in metal cutting: A neural network approach
This paper discusses the application of neural network-based pattern recognition techniques for monitoring the metal-cutting… 
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