# Decision-Tree-Algorithm

Here we explain the concept and math behind Decision Tree Algorithm, code it completely from scratch using only two libraries: numpy and pandas and implement it.

In this repository you can find following files:
1. pdf file: Decision Tree Classification in Python.pdf which is a seminary paper (under the work) that explains the concept and math behind Decision Tree Algorithm 
2. Jupyter notebook file: Decision_Tree_Classifier.ipynb that consists the code of our Decision Tree Algorithm as well as it's two implementations(two differents datasets)
3. First dataset: iris_data.csv
4. Second dataset: iphone_purchase_records.csv

For understanding the concept and the working principle of the code please first read the pdf file.