Understanding the Influence of Hyperparameters on Text Embeddings for Text Classification Tasks

Nils Witt, Christin Seifert

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    5 Citations (Scopus)

    Abstract

    Many applications in the natural language processing domain require the tuning of machine learning algorithms, which involves adaptation of hyperparameters. We perform experiments by systematically varying hyperparameter settings of text embedding algorithms to obtain insights about the influence and interrelation of hyperparameters on the model performance on a text classification task using text embedding features. For some parameters (e.g., size of the context window) we could not find an influence on the accuracy while others (e.g., dimensionality of the embeddings) strongly influence the results, but have a range where the results are nearly optimal. These insights are beneficial to researchers and practitioners in order to find sensible hyperparameter configurations for research projects based on text embeddings. This reduces the parameter search space and the amount of (manual and automatic) optimization time.
    Original languageEnglish
    Title of host publicationResearch and Advanced Technology for Digital Libraries
    Subtitle of host publication21st International Conference on Theory and Practice of Digital Libraries, TPDL 2017, Thessaloniki, Greece, September 18-21, 2017, Proceedings
    EditorsJaap Kamps, Giannis Tsakonas, Yannis Manolopoulos, Lazaros Iliadis, Ioannis Karydis
    PublisherSpringer
    Pages193-204
    ISBN (Electronic)978-3-319-67008-9
    ISBN (Print)978-3-319-67007-2
    DOIs
    Publication statusPublished - 2017
    Event21st International Conference on Theory and Practice of Digital Libraries 2017 - Grand Hotel Palace, Thessaloniki, Thessaloniki, Greece
    Duration: 18 Sep 201721 Sep 2017
    Conference number: 21
    http://www.tpdl.eu/tpdl2017/

    Publication series

    NameLecture Notes in Computer Science
    Volume10450

    Conference

    Conference21st International Conference on Theory and Practice of Digital Libraries 2017
    Abbreviated titleTPDL 2017
    CountryGreece
    CityThessaloniki
    Period18/09/1721/09/17
    Internet address

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  • Cite this

    Witt, N., & Seifert, C. (2017). Understanding the Influence of Hyperparameters on Text Embeddings for Text Classification Tasks. In J. Kamps, G. Tsakonas, Y. Manolopoulos, L. Iliadis, & I. Karydis (Eds.), Research and Advanced Technology for Digital Libraries: 21st International Conference on Theory and Practice of Digital Libraries, TPDL 2017, Thessaloniki, Greece, September 18-21, 2017, Proceedings (pp. 193-204). (Lecture Notes in Computer Science; Vol. 10450). Springer. https://doi.org/10.1007/978-3-319-67008-9_16