task_categories:tabular-classification size_categories:n<1k language:en license:cc glass tabular_classification binary_classification UCI region:us
@misc{misc_glass_efficiency_242,
  author       = {Tsanas,Athanasios & Xifara,Angeliki},
  title        = {{Glass efficiency}},
  year         = {2012},
  howpublished = {UCI Machine Learning Repository},
  note         = {{DOI}: \\url{10.24432/C51307}}
}
---
language:
- en
tags:
- glass
- tabular_classification
- binary_classification
- UCI
pretty_name: Glass evaluation
size_categories:
- n<1k
task_categories:
- tabular-classification
configs:
- glass
- windows
- vehicles
- containers
- tableware
- headlamps
license: cc
---
# Glass
The [Glass dataset](https://archive-beta.ics.uci.edu/dataset/42/glass+identification) from the [UCI repository](https://archive-beta.ics.uci.edu).
Classify the type of glass.

# Configurations and tasks
| **Configuration** | **Task**                  | **Description**          |
|-------------------|---------------------------|--------------------------|
| glass             | Multiclass classification | Classify glass type.     |
| windows           | Binary classification     | Is this windows glass?   |
| vehicles          | Binary classification     | Is this vehicles glass?  |
| containers        | Binary classification     | Is this containers glass?|
| tableware         | Binary classification     | Is this tableware glass? |
| headlamps         | Binary classification     | Is this headlamps glass? |



# Usage
```python
from datasets import load_dataset

dataset = load_dataset("mstz/glass", "glass")["train"]
```