https://github.com/snehankekre/streamlit-yellowbrick
Streamlit component for the Yellowbrick visualization and model diagnostics library
https://github.com/snehankekre/streamlit-yellowbrick
data-visualization machine-learning matplotlib python scikit-learn streamlit visualization yellowbrick
Last synced: 8 months ago
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Streamlit component for the Yellowbrick visualization and model diagnostics library
- Host: GitHub
- URL: https://github.com/snehankekre/streamlit-yellowbrick
- Owner: snehankekre
- License: mit
- Created: 2021-06-08T09:25:24.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-07-08T04:46:17.000Z (over 4 years ago)
- Last Synced: 2025-01-31T02:22:50.114Z (9 months ago)
- Topics: data-visualization, machine-learning, matplotlib, python, scikit-learn, streamlit, visualization, yellowbrick
- Language: Python
- Homepage: https://share.streamlit.io/snehankekre/streamlit-yellowbrick/examples/app.py
- Size: 119 KB
- Stars: 13
- Watchers: 3
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
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README
# streamlit-yellowbrick
[](https://share.streamlit.io/snehankekre/streamlit-yellowbrick/examples/app.py)
This component provides a convenience function to display [Yellowbrick](https://www.scikit-yb.org/en/latest/index.html) [visualizers](https://www.scikit-yb.org/en/latest/api/index.html) in Streamlit.
## Installation
`pip install streamlit-yellowbrick`
## Example usage
```python
import streamlit as st
from streamlit_yellowbrick import st_yellowbrickfrom yellowbrick.datasets import load_credit
from yellowbrick.features import PCA# Specify the features of interest and the target
X, y = load_credit()
classes = ['account in default', 'current with bills']visualizer = PCA(scale=True, classes=classes)
visualizer.fit_transform(X, y) # Fit the data to the visualizer
st_yellowbrick(visualizer) # Finalize and render the figure
```