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LOOCLASS: Stata module for generating classification statistics of Leave-One-Out cross-validation for binary outcomes

Author

Listed:
  • Ariel Linden

    (Linden Consulting Group, LLC)

Programming Language

Stata

Abstract

looclass performs leave-one-out cross-validation for regression and machine learning models with a binary outcome and then produces classification measures to assist in determining the error rate (or conversely, the accuracy) of a prediction (classification) model. Leave-one-out cross-validation is n-fold cross-validation, where n is the number of observations in the dataset. Each observation in turn is left out, and the given model is estimated for all remaining observations. The predicted value is then calculated for the one hold-out observation, and the accuracy is determined as success or failure in predicting the outcome for that observation. The results of all n predictions are used to calculate the final error estimates (accuracy) displayed in the classification table and ROC analyses generated by looclass.

Suggested Citation

  • Ariel Linden, 2015. "LOOCLASS: Stata module for generating classification statistics of Leave-One-Out cross-validation for binary outcomes," Statistical Software Components S458032, Boston College Department of Economics, revised 26 Feb 2024.
    • Handle: RePEc:boc:bocode:s458032
    Note: This module should be installed from within Stata by typing "ssc install looclass". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/l/looclass.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/l/looclass.sthlp
    File Function: help file
    Download Restriction: no
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