In this study, we approached the Hit Song Prediction problem, which aims to predict which songs will become Billboard hits. We gathered a dataset of nearly 18500 hit and non-hit songs and extracted their audio features using the Spotify Web API. We test four machine-learning models on our dataset. We were able to predict the Billboard success of a song with approximately 86\% accuracy. The most succesful algorithms were Random Forest and Support Vector Machine.

翻译：在这项研究中,我们探讨了《点击歌曲预测》问题,其目的是预测哪些歌曲将成为广告牌点击率。我们收集了近18500首击打和非击打歌曲的数据集,并使用“点斑网络API”提取了这些歌曲的音频特征。我们在我们的数据集上测试了四种机器学习模型。我们能够以大约86 ⁇ 的准确度预测一首歌曲的广告牌成功率。最有帮助的算法是随机森林和支持矢量机。