Search results for "class discovery"

showing 2 items of 2 documents

Computation Cluster Validation in the Big Data Era

2017

Data-driven class discovery, i.e., the inference of cluster structure in a dataset, is a fundamental task in Data Analysis, in particular for the Life Sciences. We provide a tutorial on the most common approaches used for that task, focusing on methodologies for the prediction of the number of clusters in a dataset. Although the methods that we present are general in terms of the data for which they can be used, we offer a case study relevant for Microarray Data Analysis.

Clustering high-dimensional dataClass (computer programming)Clustering validation measureSettore INF/01 - InformaticaComputer sciencebusiness.industryBig dataInferenceMicroarrays data analysiscomputer.software_genreGap statisticTask (project management)ComputingMethodologies_PATTERNRECOGNITIONCURE data clustering algorithmConsensus clusteringHypothesis testing in statisticClustering Class Discovery in Data Algorithmsb Clustering algorithmFigure of meritConsensus clusteringData miningCluster analysisbusinesscomputer
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Combining Supervised and Unsupervised Learning to Discover Emotional Classes

2017

Most previous work in emotion recognition has fixed the available classes in advance, and attempted to classify samples into one of these classes using a supervised learning approach. In this paper, we present preliminary work on combining supervised and unsupervised learning to discover potential latent classes which were not initially considered. To illustrate the potential of this hybrid approach, we have used a Self-Organizing Map (SOM) to organize a large number of Electroencephalogram (EEG) signals from subjects watching videos, according to their internal structure. Results suggest that a more useful labelling scheme could be produced by analysing the resulting topology in relation t…

Computer science050109 social psychologyuser modelling02 engineering and technologyMachine learningcomputer.software_genrePersonalization0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesEmotion recognitionEEGValence (psychology)Affective computingaffective computingclass discoverybusiness.industry05 social sciencesSupervised learningPattern recognitionHybrid approachComputingMethodologies_PATTERNRECOGNITIONUnsupervised learning020201 artificial intelligence & image processingArtificial intelligencebusinesscomputercluster analysis
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