Random Forests Implementation

This is an implementation of Random Forests in Python 3 to realize its working as a regressor and as a classifier.

Classifier:

The classification example is based on Sonar dataset. The dataset can be downloaded from this link: UCI Sonar Dataset

The example can be run as: python classify.py

Regressor:

The regression example is based on facial keypoints detection dataset. The dataset can be downloaded from this link: Kaggle Facial Keypoints Detection Dataset

The example code can be run as: python regress.py

References:

For more details look at the following implementations:

• https://github.com/scikit-learn/scikit-learn/sklearn/ensemble/forest.py
• https://github.com/kevin-keraudren/randomforest-python
• https://machinelearningmastery.com/implement-random-forest-scratch-python
• https://github.com/mrgloom/Kaggle-Facial-Keypoints-Detection-Solutions