Random Forests for Regression with Missing Entries

These are the source codes used in the articles:

• Irving Gómez-Méndez & Emilien Joly (2023). On the consistency of a random forest algorithm in the presence of missing entries, Journal of Nonparametric Statistics.
• Irving Gómez-Méndez & Emilien Joly (2023). Regression with missing data, a comparison study of techniques based on random forests, Journal of Statistical Computation and Simulation.

More specific codes for the creation of the datasets with missing values, the construction of the random forests for each missing-data mechanism, etc. can be found in https://github.com/IrvingGomez/RandomForestsSimulations.

There, it is possible to find examples on its use, in particular the example Example_Anderson iris.ipynb shows most of the features.

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Example of a recursive tree with missing entries.

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License: All the codes are under the GNU GPL v3 license or any posterior version.

©️ (21-05-2021) Irving Gómez Méndez.