2020 IEEE Congress on Evolutionary Computation (CEC) 2020
DOI: 10.1109/cec48606.2020.9185641
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WEC: Weighted Ensemble of Text Classifiers

Abstract: Text classification is one of the most important tasks in the field of Natural Language Processing. There are many approaches that focus on two main aspects: generating an effective representation; and selecting and refining algorithms to build the classification model. Traditional machine learning methods represent documents in vector space using features such as term frequencies, which have limitations in handling the order and semantics of words. Meanwhile, although achieving many successes, deep learning c… Show more

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Cited by 6 publications
(5 citation statements)
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“…As in [35], the main concept of PSO is a particle involving two components: a position vector which refers to a potential solution (candidate) for the optimisation problem and a velocity vector. A set of positions were initialised as follows: w ( i 0) (i = 1, .…”
Section: E Pso (Particle Swarm Optimisation)mentioning
confidence: 99%
“…As in [35], the main concept of PSO is a particle involving two components: a position vector which refers to a potential solution (candidate) for the optimisation problem and a velocity vector. A set of positions were initialised as follows: w ( i 0) (i = 1, .…”
Section: E Pso (Particle Swarm Optimisation)mentioning
confidence: 99%
“…Combining different high performing classifiers into an ensemble proved to be an effective performance boost in a recent study [35]. The researchers found that an ensemble of models using different data representations balanced the strengths and weaknesses of each data representation.…”
Section: Ensemble Approachmentioning
confidence: 99%
“…As in [35], the equations 7 and 8 will be used in the PSO objective function to generate a macro F1 score from the collective predictions vs the true predictions. Since PSO is only set up to find minima and not maxima, the F1 score will have to be inverted (1/F1 score) before the value is returned.…”
Section: E Pso (Particle Swarm Optimisation)mentioning
confidence: 99%
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“…There are different voting schemes, such as majority voting, where the predicted class with the highest number of votes is selected, and weighted voting, where the models' predictions are weighted based on their performance or expertise. Weight-based and majority vote-based models play an important role in image classification, medicine, and manufacturing, enabling the prediction of failures and providing predictive support [30][31][32][33][34]. We used both methods in different phases to identify the more accurate results.…”
mentioning
confidence: 99%