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Binary classification

Known as: Binary classifier, Binary categorization, Binary test 
Binary or binomial classification is the task of classifying the elements of a given set into two groups on the basis of a classification rule… 
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Related topics

Related topics

35 relations
Automatic summarizationBayesian networkCalibration (statistics)Complexity

Broader (2)

Machine learningStatistical classification

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
Multitask centroid twin support vector machines
2012
2012
Classifying sentiment in arabic social networks: Naïve search versus Naïve bayes
Social networks contain large amounts of posts of different data types (text, images, sounds and videos). Textual posts express… 
2011
2011
Multi-signal gesture recognition using temporal smoothing hidden conditional random fields
We present a new approach to multi-signal gesture recognition that attends to simultaneous body and hand movements. The system… 
2007
2007
A Fast Multiple-Source Detection and Localization Array Signal Processing Algorithm Using the Spatial Filtering and ML Approach
We propose a computationally efficient algorithm for detection of multiple signals that also gives a rough estimation of their… 
2007
2007
Robust Estimation of Google Counts for Social Network Extraction
Various studies within NLP and Semantic Web use the so-called Google count, which is the hit count on a query returned by a… 
Highly Cited
2006
Highly Cited
2006
Granular SVM with Repetitive Undersampling for Highly Imbalanced Protein Homology Prediction
Highly imbalanced classification is important and increasingly common with emergence of new machine learning application domains… 
2006
2006
Biometric Verification: Looking Beyond Raw Similarity Scores
Most biometric verification techniques make decisions based solely on a score that represents the similarity of the query… 
2005
2005
Filtering-Ranking Perceptron Learning for Partial Parsing
This work introduces a general phrase recognition system based on perceptrons, and a global online learning algorithm to train… 
2005
2005
A new weighted support vector machine with GA-based parameter selection
When training sets with uneven class sizes are used, the classification error based on C-support vector machine is undesirably… 
Highly Cited
2003
Highly Cited
2003
Learning cross-document structural relationships using boosting
Multi-document discoure analysis has emerged with the potential of improving various information retrieval applications. Based on… 
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