The objective of this work was to develop and evaluate the Random Forest and the Decision Forest algorithms. This ZIP file contains all the documentation, code and datasets asked to deliver. The different contents are stored in different directories in order to make an easier way to search and store the information wanted.

The directories in this project with their content are the followings:

- Code: Contains the source code developed, the implementation of the algorithms, the preprocessing of the data, an interpreter of the trees and the main function that uses everything. The files of code that are not the main.py are stored in different directories of the project in order to have a more structured project and easier to read.

- Data: Contains the datasets evaluated on the report, in this case the datasets are: 'glass.arff', 'winequality-red.csv' and 'studentInfo.csv'.

- Documentation: This directory contains the report of the algorithms, theoretical introduction to the algorithms, pseudo-code proposed to the algorithms, and an analysis of the results obtained. There is also appended a file with the occurrences of the attributes for each combination of hyperparameters in each algorithm in all datasets.