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PickleTeam! at SemEval-2018 Task 2: English and Spanish Emoji Prediction from Tweets

2018-06-01 · SEMEVAL 2018 6 · Daphne Groot, R{\'e}mon Kruizinga, Hennie Veldthuis, Simon de Wit, Hessel Haagsma

We present a system for emoji prediction on English and Spanish tweets, prepared for the SemEval-2018 task on Multilingual Emoji Prediction. We compared the performance of an SVM, LSTM and an ensemble of these two. We found the SVM performed best on our development set with an accuracy of 61.3{\%} for English and 83{\%} for Spanish. The features used for the SVM are lowercased word n-grams in the range of 1 to 20, tokenised by a TweetTokenizer and stripped of stop words. On the test set, our model achieved an accuracy of 34{\%} on English, with a slightly lower score of 29.7{\%} accuracy on Spanish.

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Sigmoid Activation 설명 없음
Tanh Activation 설명 없음
SVM A Support Vector Machine, or SVM, is a non-parametric supervised learning model. For non-linear classification and regression, they utilise the kernel trick to map inputs…
LSTM An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla…

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