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    <titleInfo>
        <title>BrainEE at SemEval-2019 Task 3: Ensembling Linear Classifiers for Emotion Prediction</title>
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    <name type="personal">
        <namePart type="given">Vachagan</namePart>
        <namePart type="family">Gratian</namePart>
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            <title>Proceedings of the 13th International Workshop on Semantic Evaluation</title>
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        <name type="personal">
            <namePart type="given">Jonathan</namePart>
            <namePart type="family">May</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Shutova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Aurelie</namePart>
            <namePart type="family">Herbelot</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Xiaodan</namePart>
            <namePart type="family">Zhu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Marianna</namePart>
            <namePart type="family">Apidianaki</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Saif</namePart>
            <namePart type="given">M</namePart>
            <namePart type="family">Mohammad</namePart>
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            <publisher>Association for Computational Linguistics</publisher>
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    <abstract>The paper describes an ensemble of linear perceptrons trained for emotion classification as part of the SemEval-2019 shared-task 3. The model uses a matrix of probabilities to weight the activations of the base-classifiers and makes a final prediction using the sum rule. The base-classifiers are multi-class perceptrons utilizing character and word n-grams, part-of-speech tags and sentiment polarity scores. The results of our experiments indicate that the ensemble outperforms the base-classifiers, but only marginally. In the best scenario our model attains an F-Micro score of 0.672, whereas the base-classifiers attained scores ranging from 0.636 to 0.666.</abstract>
    <identifier type="citekey">gratian-2019-brainee</identifier>
    <identifier type="doi">10.18653/v1/S19-2020</identifier>
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        <url>https://aclanthology.org/S19-2020/</url>
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        <date>2019-06</date>
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            <start>137</start>
            <end>141</end>
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%0 Conference Proceedings
%T BrainEE at SemEval-2019 Task 3: Ensembling Linear Classifiers for Emotion Prediction
%A Gratian, Vachagan
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F gratian-2019-brainee
%X The paper describes an ensemble of linear perceptrons trained for emotion classification as part of the SemEval-2019 shared-task 3. The model uses a matrix of probabilities to weight the activations of the base-classifiers and makes a final prediction using the sum rule. The base-classifiers are multi-class perceptrons utilizing character and word n-grams, part-of-speech tags and sentiment polarity scores. The results of our experiments indicate that the ensemble outperforms the base-classifiers, but only marginally. In the best scenario our model attains an F-Micro score of 0.672, whereas the base-classifiers attained scores ranging from 0.636 to 0.666.
%R 10.18653/v1/S19-2020
%U https://aclanthology.org/S19-2020/
%U https://doi.org/10.18653/v1/S19-2020
%P 137-141

Markdown (Informal)

[BrainEE at SemEval-2019 Task 3: Ensembling Linear Classifiers for Emotion Prediction](https://aclanthology.org/S19-2020/) (Gratian, SemEval 2019)

• BrainEE at SemEval-2019 Task 3: Ensembling Linear Classifiers for Emotion Prediction (Gratian, SemEval 2019)

ACL

• Vachagan Gratian. 2019. BrainEE at SemEval-2019 Task 3: Ensembling Linear Classifiers for Emotion Prediction. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 137–141, Minneapolis, Minnesota, USA. Association for Computational Linguistics.