HarvardX Professional Certificate - Final Capstone IDV Project
In this IDV project, we used different machine learning algorithms to improve the prediction accuracy of Pulsars showed it to have prevalence, in favour of non pulsar stars, and that it would be hard to develop manual rules to accurately predict some of the Pulsars. The highest accuracy of 98.16% was obtained using the Decision Trees algorithm while the highest F1 Score of 93% was also obtained using the Naive Bayes algorithm.
pulsar_stars.csv - This .csv file and source data for the project, originated from "Kaggle", "https://www.kaggle.com/pavanraj159/predicting-a-pulsar-star"
PulsarStar-code.R - The main R file for this project.
PulsarStar.rmd - This .rmd file creates a fully reproducible report whose final .pdf output is below.
PulsarStar.pdf - Final Project .pdf file