keerthikoganti/pens-markers-tabular-dataset-2025

Dataset Card for keerthikoganti/pens-markers-tabular-dataset-2025

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Dataset Details

Dataset Description

<!-- Provide a longer summary of what this dataset is. --> This dataset contains measurements and categorical attributes of common pens like Pilot, Bic, Sharpie. It was created as a class exercise for supervised learning on tabular data, supporting both regression by predicting line width and classification such as “thick vs. thin” line.

• —Curated by: Fall 2025 24-679 course at Carnegie Mellon University
• —Shared by : Keerthi Koganti
• —Language(s) (NLP): English
• —License: Carnegie Mellon

Uses

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Direct Use

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Classification: predict LineWidthBinary thick vs. thin line.

Regression: predict LineWidthmm from brand/type/ink color and physical attributes.

Created table of different pen types, brands

Out-of-Scope Use

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Generalization to all pen marker products or manufacturing.

Any safety-critical or commercial application.

Dataset Structure

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This dataset currently includes an original split a single table.Then included an augmented split jitter and categorical bootstrapping with constraint and decision-boundary.

Dataset Creation

Curation Rationale

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Provide students with a concrete, physical-world tabular dataset that supports both regression and classification while remaining easy to collect and measure.

Source Data

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Data Collection and Processing

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Data Collection: Measurements taken from commonly available pens and markers.

Labels: LineWidthBinary derived from LineWidthmm using a preset threshold

Processing: Basic cleaning and integer encoding of categorical fields Type, Ink Color.

Who are the source data producers?

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Original data: Keerthi Koganti

Augmented data: generated with jitter and categorical bootstrapping with constraint and decision-boundary consistency

Bias, Risks, and Limitations

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Small sample size: Limited number of instruments and brands.

Domain bias: Brands,types,colors reflect items readily available to collectors, not the full market.

Recommendations

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Use primarily for teaching and demonstration of tabular ML workflows.

If you publish results, disclose the line-width threshold, measurement protocol such as what device used.

Dataset Card Contact

Keerthi Koganti- kkoganti@andrew.cmu.edu