Datasets:
annotations_creators:
- found
language_creators:
- found
language:
- en
license: mit
multilinguality: monolingual
size_categories:
- 100<n<1K
source_datasets:
- original
task_categories:
- tabular-classification
pretty_name: ImageDataHW1
Dataset Card for TabularDataHW1
This dataset contains tabular data describing classical music pieces by Beethoven and Mozart, for classification by composer.
Dataset Details
Dataset Description
The original split consists of 30 classical piano pieces, for prediction of whether the composer is either Mozart or Beethoven. The five parameters measured were number of right hand notes, number of left hand notes, number of measures, key center, and marking data. The data was augmented 120 rows of Jittering, 90 rows of Mixup, and 90 rows of CTGAN. Google Gemini was used for code debugging only.
Curated by: Ethan Kessler
License: MIT
Uses
Direct Use
This dataset is for use in training a classifier model on tabular data
Out-of-Scope Use
More Information Needed
Dataset Structure
The original split consists of 30 classical piano pieces, for prediction of whether the composer is either Mozart or Beethoven. The five parameters measured were number of right hand notes, number of left hand notes, number of measures, key center, and marking data. The labels for the key center are as follows: "A": 0, "Bb": 1, "B": 2, "C": 3, "Db": 4, "D": 5, "Eb": 6, "E": 7, "F": 8, "Gb": 9, "G": 10, "Ab": 11 The labels for the marking data is as follows: 0 = Minuet 1 = Allegro 2 = Andante 3 = Moderato 4 = Allegretto 5 = Dance The data was augmented, using 303 rows of EDA, 202 rows of character level noise, 303 rows of backtranslation, and 202 rows of paraphrasing.
Dataset Creation
Curation Rationale
More Information Needed
Source Data
Data Collection and Processing
The data was collected manually by the dataset author using the recommendation of Microsoft Copilot to select pieces, and open source sheet music was used for analysis.
Who are the source data producers?
Annotations [optional]
Labeling process
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Who are the annotators?
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Personal and Sensitive Information
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Bias, Risks, and Limitations
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Recommendations
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
Dataset Card Contact
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