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C_ML_STATA_CV: Stata module to implement machine learning classification in Stata

Author

Listed:
  • Giovanni Cerulli

    (IRCrES-CNR)

Programming Language

Stata

Abstract

c_ml_stata is a command for implementing machine learning classification algorithms in Stata 16. It uses the Stata/Python integration (sfi) capability of Stata 16 and allows to implement the following classification algorithms: tree, boosting, random forest, regularized multinomial, neural network, naive Bayes, nearest neighbor, support vector machine. It provides hyper-parameters' optimal tuning via K-fold cross-validation using greed search. For each observation (or instance), this command generates both predicted class probabilities and predicted labels using the Bayes classification rule. This command makes use of the Python Scikit-learn API to carry out both cross-validation and prediction.

Suggested Citation

  • Giovanni Cerulli, 2022. "C_ML_STATA_CV: Stata module to implement machine learning classification in Stata," Statistical Software Components S459055, Boston College Department of Economics, revised 16 Nov 2022.
  • Handle: RePEc:boc:bocode:s459055
    Note: This module should be installed from within Stata by typing "ssc install c_ml_stata_cv". 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

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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_ml_stata_cv.ado
    File Function: program code
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_ml_stata_default.ado
    File Function: program code
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_ml_stata_cv.sthlp
    File Function: help file
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    File URL: http://fmwww.bc.edu/repec/bocode/p/pylearn.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/r/r_ml_stata_cv.sthlp
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    File URL: http://fmwww.bc.edu/repec/bocode/g/get_train_test.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/g/get_train_test.sthlp
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_boost.py
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_naivebayes.py
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_nearestneighbor.py
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_neuralnet.py
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_randomforest.py
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_regularizedmultinomial.py
    File Function: program code
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_multinomial.py
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_svm.py
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    File URL: http://fmwww.bc.edu/repec/bocode/c/c_tree.py
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    File URL: http://fmwww.bc.edu/repec/bocode/e/example_c_ml_stata.do
    File Function: sample file
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    File URL: http://fmwww.bc.edu/repec/bocode/d/data_new_x.dta
    File Function: sample data file
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    File URL: http://fmwww.bc.edu/repec/bocode/d/data_new_y.dta
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