TabularDataHW1 / README.md
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---
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
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
More Information Needed
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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
<!-- Motivation for the creation of this dataset. -->
More Information Needed
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
### Annotations [optional]
<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
#### Labeling process
<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
More Information Needed
#### Who are the annotators?
<!-- This section describes the people or systems who created the annotations. -->
More Information Needed
#### Personal and Sensitive Information
<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
More Information Needed
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
More Information Needed]
### Recommendations
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
## Dataset Card Contact
More Information Needed