Datasets:
metadata
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 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
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 |