BeataWereszczynska / SML_forged_banknotes

Comparison of numerous supervised machine learning classifier models (Logistic Regression, K-Nearest Neighbors, Support Vector Machines and Decision Trees) predicting if a banknote is genuine or not based on the dataset from OpenML containing wavelet analysis results for genuine and forged banknotes. (Python 3)

SML_forged_banknotes

Comparison of numerous supervised machine learning classifier models (Logistic Regression, K-Nearest Neighbors, Support Vector Machines and Decision Trees) predicting if a banknote is genuine or not based on the dataset from OpenML containing wavelet analysis results for genuine and forged banknotes.

The repository contains:

1. Jupyter notebook SML_forged_banknotes.ipynb with all the python code, visualizations, results and commentaries.
2. Data file Banknote-authentication-dataset.csv.

Data reference

Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

Available at https://www.openml.org/search?type=data&sort=runs&id=1462&status=active.

License

The project is licensed under the MIT license. See the LICENSE file for license rights and limitations.

You may also like

UML_forged_banknotes - Unsupervised machine learning dimensionality reduction and clustering models for predicting if a banknote is genuine or not based on the dataset from OpenML containing wavelet analysis results for genuine and forged banknotes - practical exercise (https://github.com/BeataWereszczynska/UML_forged_banknotes).