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.