Implementation of Decision Tree classification algorithm in Python using Pandas, NumPy and Scikit-Learn.
Classifier is being tested on sklearn "toy" datasets:
- Iris plant dataset
- Optical recognition of handwritten digits dataset
- Wine recognition dataset
- Breast cancer wisconsin (diagnostic) dataset
Each dataset is being tested with manual/sklearn classifiers with gini/entropy criteria.
Graphviz library is used to visualize decision trees for each case.