Multi-Classifier System for Sentiment Analysis and Opinion Mining

Batista, Luana; Ratté, Sylvie

doi:10.1007/978-1-4614-7163-9_351-1

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Multiple-classifier Systems1

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2022

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Cited by 2 publications

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“…In the field of people detection, several authors have used multi-classifier approaches: [22] use Histograms of Oriented Gradients (HOGs) and Local Receptive Fields (LRFs), which are provided by a convolutional neural network, and are classified by Multi-Layer Perceptrons (MLPs) and Support Vector Machines (SVMs) combining classifiers by majority vote and fuzzy integral; [23,24,25] present a MCS to manage image based classification problems; Batista et al [26], take advantage of unigrams, bigrams and trigrams to design a Multiple-Classifier System for Sentiment Analysis and Opinion Mining.…”

Section: Multiple-classifier Systemsmentioning

confidence: 99%