| --- |
| dataset_info: |
| features: |
| - name: source_id |
| dtype: string |
| - name: part_function |
| dtype: string |
| - name: max_length |
| dtype: float64 |
| - name: max_width |
| dtype: float64 |
| - name: max_depth |
| dtype: float64 |
| - name: symmetry |
| dtype: string |
| - name: material |
| dtype: string |
| - name: base_sketch_shape |
| dtype: string |
| - name: parent_id |
| dtype: string |
| - name: augmentation |
| dtype: string |
| - name: is_augmented |
| dtype: bool |
| - name: second_parent_id |
| dtype: string |
| - name: mix_weight |
| dtype: float64 |
| splits: |
| - name: train |
| num_bytes: 54717 |
| num_examples: 336 |
| - name: validation |
| num_bytes: 537 |
| num_examples: 4 |
| - name: test |
| num_bytes: 682 |
| num_examples: 5 |
| download_size: 29657 |
| dataset_size: 55936 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: validation |
| path: data/validation-* |
| - split: test |
| path: data/test-* |
| language: |
| - en |
| task_categories: |
| - tabular-classification |
| pretty_name: CAD Feature Dataset (Tabular) |
| tags: |
| - tabular |
| - cad |
| - 24-679 |
| - data-augmentation |
| --- |
| |
| # CAD Model Features Dataset (Text-to-CAD Focus) |
|
|
| `OmarK211/tabular-test` |
|
|
| A tabular dataset of CAD model geometric and functional parameters, containing manually collected samples (`original`) and synthetic variants (`augmented`). |
|
|
| ## Task Overview |
|
|
| The primary predictive target is **`base_sketch_shape`** (categorical 2D profile shape) based on 6 input dimensions and properties. |
|
|
| ## Dataset Structure & Fields |
|
|
| | Field Name | Data Type | Role | Description | |
| |---|---|---|---| |
| | `base_sketch_shape` | Categorical | Target | Core 2D profile shape (e.g., circle, rectangle, L-shape) | |
| | `max_length` | Numeric (Float) | Feature | Continuous maximum length dimension | |
| | `max_width` | Numeric (Float) | Feature | Continuous maximum width dimension | |
| | `max_depth` | Numeric (Float) | Feature | Continuous maximum depth dimension | |
| | `part_function` | Categorical | Feature | Functional role of the CAD model | |
| | `symmetry` | Categorical | Feature | Symmetry type (e.g., planar, rotational, none) | |
| | `material` | Categorical | Feature | Intended material composition | |
| | `source_id`, `parent_id`, `second_parent_id` | String | Provenance | Unique row ID and original parent source IDs | |
| | `augmentation`, `is_augmented`, `mix_weight` | Metadata | Provenance | Augmentation method, synthetic flag, and Mixup interpolation weight | |
|
|
| ## Dataset Splits |
|
|
| | Split | Original rows | Synthetic rows | Total rows | |
| |---|---:|---:|---:| |
| | `train` | 21 | 315 | 336 | |
| | `validation` | 4 | 0 | 4 | |
| | `test` | 5 | 0 | 5 | |
|
|
|
|
|
|
| ### Target Class Distribution (`base_sketch_shape`) |
|
|
| | Split | Base Sketch Shape | Rows | |
| |---|---|---:| |
| | `train` | amorphous | 32 | |
| | `train` | circular | 160 | |
| | `train` | rectangular | 144 | |
| | `validation` | amorphous | 2 | |
| | `validation` | circular | 1 | |
| | `validation` | rectangular | 1 | |
| | `test` | circular | 1 | |
| | `test` | rectangular | 4 | |
|
|
| ## Augmentation Methods |
|
|
| Synthetic samples were generated using **5** copy requests per method: |
|
|
| | Augmentation method | Retained synthetic rows | |
| |---|---:| |
| | `additive_numeric_jitter` | 105 | |
| | `mixup_interpolation` | 105 | |
| | `multiplicative_numeric_scale` | 105 | |
|
|
| - **Additive Numeric Jitter:** Applied Gaussian noise to continuous CAD dimensions (`max_length`, `max_width`, `max_depth`), clipped at positive bounds (>0.01). |
| - **Multiplicative Numeric Scaling:** Scaled continuous dimensions independently by uniform factors in [0.90, 1.10]. |
| - **Mixup Interpolation:** Linearly interpolated continuous dimensions between distinct parents using weights in [0.60, 0.90], retaining the primary parent's categorical fields. |
|
|
|
|
| ## Intended use and limitations |
|
|
| Use for teaching/learning mixed-type data contracts, provenance, augmentation, and small-sample regression. |
| This convenience sample does not represent the general population. |
|
|
| ## Privacy and licensing |
|
|
| No license was specified in repository metadata when this card was first added; this card does not assign one. |
|
|
| ## Load and compare |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("OmarK211/tabular-test") |
| # Train with ds["train"], choose settings with ds["validation"], then score ds["test"]. |
| ``` |
|
|
| Use an account with access if repository visibility changes. For reproducible comparisons, record the |
| dataset commit and model/environment versions. Regenerate this card with the preparation notebook after |
| changing the data; its counts are calculated from the actual packaged splits. The YAML schema and split |
| configuration are preserved from the upload. |
|
|
