# Dance Hit Song Prediction

## TL;DR

This paper develops and evaluates machine learning models to predict whether dance songs will become top 10 hits, using a comprehensive dataset with musical features from 1985 to 2013.

## Contribution

It introduces a new dataset of dance hits with advanced temporal features and compares multiple classifiers for hit song prediction.

## Key findings

- Best model accurately predicts top 10 dance hits
- Temporal features improve prediction performance
- Multiple classifiers tested with varying success

## Abstract

Record companies invest billions of dollars in new talent around the globe each year. Gaining insight into what actually makes a hit song would provide tremendous benefits for the music industry. In this research we tackle this question by focussing on the dance hit song classification problem. A database of dance hit songs from 1985 until 2013 is built, including basic musical features, as well as more advanced features that capture a temporal aspect. A number of different classifiers are used to build and test dance hit prediction models. The resulting best model has a good performance when predicting whether a song is a "top 10" dance hit versus a lower listed position.