Machine Learning for Navel Discharge Review

This research project aims to predict the outcome of the Naval Discharge Review Board decision for an applicant based on factors in the application, using Machine Learning techniques. The study explores three popular machine learning algorithms: MLP, Adaboost, and KNN, with KNN providing the best results. The training is verified through hyperparameter optimization and cross fold validation.

Additionally, the study investigates the ability of ChatGPT's API to classify the data that couldn't be classified manually. A total of over 8000 samples were classified by ChatGPT's API, and an MLP model was trained using the same hyperparameters that were found to be optimal for the 3000 size manual sample.The model was then tested on the manual sample. The results show that the model trained on data labeled by ChatGPT performed equivalently, suggesting that ChatGPT's API is a promising tool for labeling in this domain.