Year Prediction MSD
Donated on 2/6/2011
Prediction of the release year of a song from audio features. Songs are mostly western, commercial tracks ranging from 1922 to 2011, with a peak in the year 2000s.
Dataset Characteristics
Multivariate
Subject Area
Other
Associated Tasks
Regression
Feature Type
Real
# Instances
515345
# Features
-
Dataset Information
Additional Information
You should respect the following train / test split: train: first 463,715 examples test: last 51,630 examples It avoids the 'producer effect' by making sure no song from a given artist ends up in both the train and test set.
Has Missing Values?
No
Variables Table
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0 to 10 of 90
Additional Variable Information
90 attributes, 12 = timbre average, 78 = timbre covariance The first value is the year (target), ranging from 1922 to 2011. Features extracted from the 'timbre' features from The Echo Nest API. We take the average and covariance over all 'segments', each segment being described by a 12-dimensional timbre vector.
Dataset Files
| File | Size |
|---|---|
| YearPredictionMSD.txt | 427.8 MB |
Papers Citing this Dataset
Sort by Year, desc
By Othmane Sebbouh, Nidham Gazagnadou, Samy Jelassi, Francis Bach, Robert Gower. 2019
Published in ArXiv.
By Shikhar Bhardwaj, Ryan Curtin, Marcus Edel, Yannis Mentekidis, Conrad Sanderson. 2018
Published in ArXiv.
By Martin Jankowiak. 2018
Published in ArXiv.
By Oren Zeev-Ben-Mordehai, Wouter Duivesteijn, Mykola Pechenizkiy. 2018
Published in ArXiv.
By Nuwan Ferdinand, Stark Draper. 2018
Published in ArXiv.
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset year_prediction_msd = fetch_ucirepo(id=203) # data (as pandas dataframes) X = year_prediction_msd.data.features y = year_prediction_msd.data.targets # metadata print(year_prediction_msd.metadata) # variable information print(year_prediction_msd.variables)
Bertin-Mahieux, T. (2011). Year Prediction MSD [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C50K61.
Keywords
Creators
T. Bertin-Mahieux
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.