A series of classification models and their accuracies for predicting the genre of different types of music based off of characteristics such as their popularity, danceability, energy, key, loudness, mode, speechiness, acousticness, instrumentalness, liveness, valence, tempo, duration_in.min.ms, and time_signature.
Based off of my findings throughout the report, the neural network was the best model. By adding more layers to the neural network, the accuracy would increase, however, I ran out of time to do so. Logistic regression also performed better than random forest, but there is still very little statistial signifigance in either of the models.
The dataset used for this project can be found here.