Sökning: "Sung-Min Yang"

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  1. 1. Exploit Unlabeled Data with Language Model for Text Classification. Comparison of four unsupervised learning models

    Master-uppsats, Göteborgs universitet/Institutionen för filosofi, lingvistikoch vetenskapsteori

    Författare :Sung-Min Yang; [2018-10-29]
    Nyckelord :Text classification; Semi-supervised learning; Unsupervised learning; Transfer learning; Natural Language Processing;

    Sammanfattning : Within a situation where Semi-Supervised Learning (SSL) is available to exploit unlabeled data, this paper shows that Language Model (LM) outperforms the three models in text classification, which three models are based on Term-Frequency Inverse Document Frequency (Tf-idf) and two pre-trained word vectors. The experimental results show that the LM outperforms the other three unsupervised learning models whether the task is easy or difficult, which the difficult task consists of imbalanced data. LÄS MER