  In this work, we attempt to solve the Hit Song Science problem, which aims to
predict which songs will become chart-topping hits. We constructed a dataset
with approximately 1.8 million hit and non-hit songs and extracted their audio
features using the Spotify Web API. We test four models on our dataset. Our
best model was random forest, which was able to predict Billboard song success
with 88% accuracy.
