---
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`        |