Data
Electronic-Music-Features---201802-BeatportTop100

Electronic-Music-Features---201802-BeatportTop100

active ARFF Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Context Electronic dance music (EDM) is a genre where thousands of new songs are released every week. The list of EDM subgenres considered is long, but it also evolves according to trends and musical tastes. With this in view, we have retrieved two sets of over 2,000 songs separated by more than a year. Songs belong to the top 100 list of an EDM website taxonomy of more than 20 subgenres that changed in the period considered. Content Each row is an electronic music song. The dataset contains 100 song for each genre among Beatport electronic music genres, they were the top (100) songs of their genres on November 2018. Columns are audio features extracted of a two random minutes sample of the file audio. These features have been extracted using pyAudioAnalysis (https://github.com/tyiannak/pyAudioAnalysis). Acknowledgements Special thanks to the people who made this possible. Javier Arroyo, Laura Prez-Molina y Jaime Snchez-Hernndez. Inspiration These datasets are used in this publication "Automatic subgenre classication in an electronic dance music taxonomy " where we test the effectiveness of automatic classification on these sets and delve into the results.

94 features

Unnamed:_0numeric2900 unique values
0 missing
1-ZCRmnumeric2812 unique values
0 missing
2-Energymnumeric2812 unique values
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3-EnergyEntropymnumeric2812 unique values
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4-SpectralCentroidmnumeric2812 unique values
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5-SpectralSpreadmnumeric2812 unique values
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6-SpectralEntropymnumeric2812 unique values
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7-SpectralFluxmnumeric2812 unique values
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8-SpectralRolloffmnumeric2812 unique values
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9-MFCCs1mnumeric2812 unique values
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74-bpm_histogram_second_peak_bpmnumeric52 unique values
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77-danceabilitynumeric2811 unique values
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78-beats_loudness.meannumeric2812 unique values
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Show all 94 features

19 properties

NumberOfInstances
2900
Number of instances (rows) of the dataset.
NumberOfFeatures
94
Number of attributes (columns) of the dataset.
NumberOfClasses
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
93
Number of numeric attributes.
NumberOfSymbolicFeatures
0
Number of nominal attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
AutoCorrelation
Average class difference between consecutive instances.
PercentageOfNumericFeatures
98.94
Percentage of numeric attributes.
Dimensionality
0.03
Number of attributes divided by the number of instances.
PercentageOfSymbolicFeatures
0
Percentage of nominal attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
MajorityClassSize
Number of instances belonging to the most frequent class.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
0
Number of binary attributes.
Show all 19 properties

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