Decision trees and random forest

### Description

>Decision Trees (DTs) are a non-parametric supervised learning method used for [classification](https://scikit-learn.org/stable/modules/tree.html#tree-classification) and [regression](https://scikit-learn.org/stable/modules/tree.html#tree-regression) [3].

The random forest algorithm is a supervised classification algorithm. Pseudocode is given in [1] and [2]. Sadly I cannot provide any more information about that. If you worked with random forests yourself, you may make more sense out the publications than I would in this short description.

### References
- [1] https://pages.cs.wisc.edu/~matthewb/pages/notes/pdf/ensembles/RandomForests.pdf
- [2] https://www.researchgate.net/publication/362631001_Feature_selection_and_computational_optimization_in_high-dimensional_microarray_cancer_datasets_via_InfoGain-modified_bat_algorithm
- [3] https://scikit-learn.org/stable/modules/tree.html#decision-trees