| --- |
| license: mit |
| task_categories: |
| - tabular-classification |
| language: |
| - en |
| tags: |
| - synthetic |
| - sparse-learning |
| - classification |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # is_sparse/sparse5d |
| |
| ## Dataset Description |
| |
| This is a synthetic 5-dimensional classification dataset designed for sparse learning research. |
| The dataset contains 3 classes and is specifically designed to have sparse optimal representations, |
| where only a subset of features are informative for the classification task. |
| |
| ### Dataset Summary |
| |
| - **Variant**: sparse5d |
| - **Features**: 5 continuous features |
| - **Classes**: 3 |
| - **Entropy(Y)**: 1.4855 |
| - **Mutual Information (joint)**: 1.1819 |
| - **Maximum Achievable Accuracy**: 0.8967 |
| |
| |
| ## Dataset Structure |
| |
| ### Data Instances |
| |
| Each instance consists of: |
| - `data`: A 5-dimensional feature vector (float32) |
| - `label`: An integer class label (0, 1, or 2) |
| |
| ### Data Splits |
| |
| | Split | Number of Instances | |
| |-------|---------------------| |
| | Train | Variable (see below) | |
| | Test | Variable (see below) | |
| |
| ## Dataset Creation |
| |
| This dataset was synthetically generated for research on sparse learning and optimal feature selection. |
| The mutual information values between feature subsets and labels are provided in the metadata. |
| |
| ### Mutual Information Structure |
| |
| The dataset includes ground-truth mutual information values for various feature subsets, enabling: |
| - Feature importance analysis |
| - Information-theoretic learning algorithms |
| - Benchmarking of MI estimation methods |
| |
| Key MI values: |
| - joint: 1.1819 |
| - 1: 0.3273 |
| - 1-2: 0.3273 |
| - 1-2-3: 0.6634 |
| - 1-2-3-4: 0.6634 |
| - 1-2-3-4-5: 1.1819 |
| - 1-2-3-5: 1.1819 |
| - 1-2-4: 0.3273 |
| - 1-2-4-5: 1.0492 |
| - 1-2-5: 1.0492 |
| |
| ## Citation |
| |
| If you use this dataset, please cite the associated research paper (to be added). |
| |
| ## License |
| |
| MIT License |
| |
