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