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The Proportion for Splitting Data into Training and Test Set for the Bootstrap in Classification Problems

Author

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  • Vrigazova Borislava

    (Sofia University, Faculty of Economics and Business Administration, Bulgaria)

Abstract

Background: The bootstrap can be alternative to cross-validation as a training/test set splitting method since it minimizes the computing time in classification problems in comparison to the tenfold cross-validation.

Suggested Citation

  • Vrigazova Borislava, 2021. "The Proportion for Splitting Data into Training and Test Set for the Bootstrap in Classification Problems," Business Systems Research, Sciendo, vol. 12(1), pages 228-242, May.
    • Handle: RePEc:bit:bsrysr:v:12:y:2021:i:1:p:228-242:n:9
    DOI: 10.2478/bsrj-2021-0015
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    References listed on IDEAS

    as
    1. Borislava Petrova Vrigazova & Ivan Ganchev Ivanov, 2020. "The bootstrap procedure in classification problems," International Journal of Data Mining, Modelling and Management, Inderscience Enterprises Ltd, vol. 12(4), pages 428-446.
    2. James G. MacKinnon, 2002. "Bootstrap inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 35(4), pages 615-645, November.
    3. Grubinger, Thomas & Zeileis, Achim & Pfeiffer, Karl-Peter, 2014. "evtree: Evolutionary Learning of Globally Optimal Classification and Regression Trees in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i01).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    the bootstrap; classification; cross-validation; repeated train/test splitting;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

    Statistics

    Access and download statistics

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