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--- |
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language: |
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- en |
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tags: |
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- student performance |
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- tabular_classification |
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- multiclass_classification |
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- UCI |
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pretty_name: Diamond |
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size_categories: |
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- 10K<n<100K |
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task_categories: |
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- tabular-classification |
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configs: |
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- encoding |
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- cut |
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- cut_binary |
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license: cc |
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--- |
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# Diamonds |
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The [Diamonds dataset](https://www.kaggle.com/datasets/ulrikthygepedersen/diamonds) from Kaggle. |
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Dataset collecting properties of cut diamonds to determine the cut quality. |
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# Configurations and tasks |
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| **Configuration** | **Task** | Description | |
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|-------------------|---------------------------|-----------------------------------------------------------------| |
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| encoding | | Encoding dictionary showing original values of encoded features.| |
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| cut | Multiclass classification | Predict the cut quality of the diamond. | |
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| cut_binary | Binary classification | Is the cut quality at least very good?| |
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# Usage |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("mstz/diamonds", "cut")["train"] |
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``` |
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# Features |
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|**Feature** |**Description**| |
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|-----------------------------------|---------------| |
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|`carat` | `float32` | |
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|`color` | `string` | |
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|`clarity` | `float32` | |
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|`depth` | `float32` | |
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|`table` | `float32` | |
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|`price` | `float32` | |
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|`observation_point_on_axis_x` | `float32` | |
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|`observation_point_on_axis_y` | `float32` | |
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|`observation_point_on_axis_z` | `float32` | |
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|`cut` | `int8` | |
