PunditKit: A GUI for Scikit-Learn Models
Simplify. Visualise. Learn.
PunditKit is a toolkit for training machine learning models on tabular data simply and without code. It is intended for students and experienced data scientists who are looking to quickly obtain some initial predictive insights from data.
- Machine learning using scikit-learn
- Interpretable explanations of predictions using lime
- Exploratory data summaries and model performance on holdout data for checks
- Partial dependence plots
PunditKit is under active development. The goal is to develop an opinionated modelling framework with best practice modelling and visualisation. If you encounter any problems, please raise an issue.
Installation (via pip)
PunditKit is developed using Python. First download and install a Python 3.x distribution such as Anaconda
PunditKit can then be installed using
pip from the command line (if
is added to PATH during installation) or using Anaconda prompt.
pip install punditkit
This adds the
Modelling a dataset
Suppose you have a file called
iris.csv that you would like to model.
To use punditkit on the dataset, run:
Currently only Comma Separated Values (CSV) datasets are supported. For Excel spreadsheets, please Save As CSV to analyse using punditkit.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
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