Classification-of-Data-with-Random-Forests-and-Decision-Trees

Random Forest Classification of data based on entropy, using RandomForestClassifier from Sci-Kit Learn module.

Requirements

Python 3.6 and above
Modules needed-
- sklearn
- pydotplus
- pandas
- matplotlib
- numpy

Install pydotplus before graphviz to avoid errors using pip.

Data

Any labelled data can be used to test for random forests and decision trees. For now used a simple Egyptian Skulls Dataset

Running Code

Execute the Decision trees and Random Forests python files respectively to check results, accuracy score and to visualize the Tree/Trees.
Random Forests can be slow depending on the data you are working with as it creates multiple decision trees using bootstrapping, bigger the data slower the process.