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Decision boundary

Known as: Decision surface, Decision surfaces 
In a statistical-classification problem with two classes, a decision boundary or decision surface is a hypersurface that partitions the underlying… 
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Related topics

Related topics

11 relations
Artificial neural networkBackpropagationGlossary of artificial intelligenceK-nearest neighbors algorithm

Broader (1)

Statistical classification

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2014
2014
A Robust Classifier for Imbalanced Datasets
Imbalanced dataset classification is a challenging problem, since many classifiers are sensitive to class distribution so that… 
2013
2013
Multiple Access and Data Reconstruction in Wireless Sensor Networks Based on Compressed Sensing
This paper considers the application of compressed sensing (CS) to a wireless sensor network for data measurement communication… 
Highly Cited
2011
Highly Cited
2011
Feature extraction and classification of EEG for automatic seizure detection
One of the many challenges in the automated detection of epileptic seizures is to draw a line of demarcation between seizure… 
2008
2008
Validation criteria for enhanced fuzzy clustering
2007
2007
A Two-Step Classification Approach to Unsupervised Record Linkage
Linking or matching databases is becoming increasingly important in many data mining projects, as linked data can contain… 
Review
1996
Review
1996
Geometric Implications of the Naive Bayes Assumption
A Naive (or Idiot) Bayes network is a network with a single hypothesis node and several observations that are conditionally… 
Highly Cited
1995
Highly Cited
1995
Pattern classification with genetic algorithms
Highly Cited
1990
Highly Cited
1990
Automated design of linear tree classifiers
1990
1990
Robust Classifiers without Robust Features
We develop a two-stage, modular neural network classifier and apply it to an automatic target recognition problem. The data are… 
1988
1988
Phoneme Recognition: Neural Networks vs
neme recognition which is characterized by two important properties: 1.) Using a 3 layer arrangement of simple computing units… 
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