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--- |
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datasets: |
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- cassieli226/lipproducts-dataset |
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tags: |
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- tabular |
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- augmentation |
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- education |
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license: cc-by-nc-sa-4.0 |
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task_categories: |
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- tabular-regression |
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--- |
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# Dataset Card for Lip Products Dataset |
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## Dataset Description |
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This dataset was collected to study relationships between physical characteristics of lip products (tube size, price, color) and their product weight (grams). |
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It was created as part of a coursework assignment on tabular dataset building and augmentation. |
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- **Repository:** [cassieli226/lipproducts-dataset](https://huggingface.co/datasets/cassieli226/lipproducts-dataset) |
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- **Author:** cassieli226 |
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- **License:** CC BY-NC-SA 4.0 |
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- **Intended Use:** Academic / coursework |
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### Dataset Summary |
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- Small tabular dataset of lip products with physical attributes and weight. |
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- Regression target: **Grams** (net product weight). |
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- Includes manually measured samples and synthetic augmentations. |
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## Supported Tasks |
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- **Regression**: Predicting product weight (grams) from physical and retail features. |
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## Dataset Structure |
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### Data Instances |
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Each row represents one lip product with its features and target weight. |
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### Data Fields |
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- `RGB` (string): Average color of the lip product in "R,G,B" format |
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- `Diameter_mm` (float): Diameter of the product tube in millimeters |
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- `Length_mm` (float): Length of the product tube in millimeters |
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- `Price` (float): Retail price in USD |
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- `Grams` (float): Net product weight in grams (target variable) |
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### Data Splits |
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- **original**: 30 manually measured samples |
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- **augmented**: 350 synthetic samples (via augmentation) |
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## Dataset Creation |
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### Source Data |
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- Collected from a personal collection of lip products. |
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- Measurements obtained with a ruler and product descriptions. |
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- RGB values extracted from swatch photos and averaged. |
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### Preprocessing and Augmentation |
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Two augmentation strategies were applied: |
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1. **Numeric Jitter** |
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- Gaussian noise added to numeric features and RGB channels (±5). |
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- Simulates natural measurement and shade variability. |
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2. **Mixup** |
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- Convex combinations of pairs of rows. |
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- Applied to numeric features and RGB values. |
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- Grams clipped to maximum physical capacity: |
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\( \text{max grams} \approx \pi \times (Diameter/2)^2 \times Length / 1000 \) |
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## Considerations for Using the Data |
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### Limitations |
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- Small initial sample size (30). |
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- Prices vary regionally and are not inflation-adjusted. |
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- RGB approximates perceived color and may differ under different lighting. |
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### Ethical Notes |
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- Dataset is non-sensitive, collected from personal items. |
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- No private or personally identifiable information is included. |
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- Augmentation constrained by physical plausibility. |
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## Additional Information |
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### Dataset Curators |
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Prepared by **cassieli226** for coursework. |
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### Licensing Information |
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**CC BY-NC-SA 4.0** |
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Free for academic and research use, not for commercial purposes. |
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### Contributions |
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ChatGPT was used to assist with **preprocessing, augmentation code (numeric jitter & mixup), and debugging**. |
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All augmentation parameters and physical constraints were designed by the dataset creator. |
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## Example Usage |
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```python |
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from datasets import load_dataset |
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ds = load_dataset("cassieli226/lipproducts-dataset") |
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print(ds) |
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print(ds["original"].to_pandas().head()) |
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##Contact: [email protected] |
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