SpotHitPy: A Study For ML-Based Song Hit Prediction Using Spotify

01/19/2023

∙

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.

READ FULL TEXT

SpotHitPy: A Study For ML-Based Song Hit Prediction Using Spotify

Song Hit Prediction: Predicting Billboard Hits Using Spotify Data

Application of Random Forest and Support Vector Machine for Investigation of Pressure Filtration Performance, a Zinc Plant Filter Cake Modeling

Yelp Review Rating Prediction: Machine Learning and Deep Learning Models

Gene Ontology (GO) Prediction using Machine Learning Methods

Using Machine Learning to Predict Poverty Status in Costa Rican Households

Recognizing Affiliation: Using Behavioural Traces to Predict the Quality of Social Interactions in Online Games

Improved prediction of soil properties with Multi-target Stacked Generalisation on EDXRF spectra

SpotHitPy: A Study For ML-Based Song Hit Prediction Using Spotify

Related Research

Song Hit Prediction: Predicting Billboard Hits Using Spotify Data

Application of Random Forest and Support Vector Machine for Investigation of Pressure Filtration Performance, a Zinc Plant Filter Cake Modeling

Yelp Review Rating Prediction: Machine Learning and Deep Learning Models

Gene Ontology (GO) Prediction using Machine Learning Methods

Using Machine Learning to Predict Poverty Status in Costa Rican Households

Recognizing Affiliation: Using Behavioural Traces to Predict the Quality of Social Interactions in Online Games

Improved prediction of soil properties with Multi-target Stacked Generalisation on EDXRF spectra