amrmoastafa / Decision-Tree

Decision Tree Algorithm from scratch

This project is a part of our coursework in Data Structure and algorithms course.

Here's the functionalities of our project: Our project can:

1. Classify any ready csv dataset after training our model
2. Parse raw text and turn it into a csv file to classify it
3. Calculate the accuracy of a pre-known classification dataset
4. Set the depth(constraint in decision tree) of the decision tree
5. Show the trained model of the tree.

And here are some screen shots demonstrating the functionalities of our GUI:

• The user can select train data (1), test or dev data (2) then check the accuracy of our tree (4) based on different input depth (3) that he may select.

• The GUI comes with an activity log to inform the user of the kind of operations taking place when he clicks a button , here the log shows a message informing the user of the result of the training of the decision tree and its output accuracy.

• The user can also select show tree to see the output tree of the given depth and its branches.

• If you want to enter a review , you can click the write a review button and write your review , either in english or in 0s and 1s , we handled both cases , then the GUI will use the generated tree to classify your review .

• Furthermore , the GUI will print the path it took to make this classification and print the classification output.

• This is a sample output based on a 3 layers' depth tree shown.