https://github.com/stevemats/pyhodophile
Interactive Py web app to explore different datasets and classifiers easily.
https://github.com/stevemats/pyhodophile
python streamlit streamlit-webapp
Last synced: about 1 month ago
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Interactive Py web app to explore different datasets and classifiers easily.
- Host: GitHub
- URL: https://github.com/stevemats/pyhodophile
- Owner: stevemats
- Created: 2021-07-25T15:17:31.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2021-07-25T17:43:01.000Z (almost 5 years ago)
- Last Synced: 2025-01-06T10:13:36.491Z (over 1 year ago)
- Topics: python, streamlit, streamlit-webapp
- Language: Python
- Homepage:
- Size: 2.31 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
## Pyhodophile:
[Pyhodophile](https://github.com/stevemats/Pyhodophile) is a web based demo py app utilizing streamlit to help you explore different datasets and classifier all in one place.
## View Demo:
https://user-images.githubusercontent.com/30528167/126907271-2ade48ff-5e80-4ab0-ba5a-c32898322600.mp4
## Definations:
**KNN**(K-Nearest Neighbors) as seen in demo above under classifiers, is a simple algorithm used in Machine Learning for regression and classification problem. It stores all available cases and classifies new cases based on a similarity measure
**Random Forest** also seen in the demo, is a machine learning technique that’s used to solve regression and classification problems. It utilizes ensemble learning, which is a technique that combines many classifiers to provide solutions to complex problems.
Finally we have **SVM**(Support Vector machine), which is a linear model for classification and regression problems. It can solve linear and non-linear problems and work well for many practical problems. The idea of SVM is simple: The algorithm creates a line or a hyperplane which separates the data into classes.
## Usage
```
streamlit run main.py
```