Candidate Hiring Prediction using Decision Tree.

A Decision Tree Classifier to predict whether a candidate applying for a job at a company would get hired or not. We created two models, one with criterion Gini index and another one with Criterion Entropy. We used Scikit-Learn for the classifier.

DataSet Name : PastHires dataset, downloaded from the UCI Machine Learning Repository website.

Dataset have 7 columns, Years Experience, Employed? Previous employers, Level of Education, Top-tier school, Interned, and Hired.

Model will predict whether the candidate would get hired by company based on the attributes of the candidate who gets hired or does not get hired from the past.

GUI is created with Python Tkinter which can give prediction for candidate individual's attribute values.

For generation Decision Tree, import module pydotplus.

$pip install pydotplus