GitHub topics: banknote-authentication

Repositories

nurulashraf/kmeans-counterfeit-bills

K-means clustering analysis of banknote dimensions for counterfeit detection. Using standardised length and diagonal measurements, the model successfully identifies three distinct clusters, with one clearly representing counterfeit bills based on their dimensional anomalies.

Language: Jupyter Notebook - Size: 598 KB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 0 - Forks: 0

KhaledAshrafH/KNN-Classifier

This repository contains a Python implementation of a K-Nearest Neighbors (KNN) classifier from scratch. It's applied to the "BankNote_Authentication" dataset, which consists of four features (variance, skew, curtosis, and entropy) and a class attribute indicating whether a banknote is real or forged.

Language: Python - Size: 63.5 KB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

KhaledAshrafH/DT-Banknote-Authenticator

This Python code utilizes the decision tree algorithm from the scikit-learn library to perform banknote authentication. The code aims to analyze the impact of different train-test split ratios and training set sizes on the accuracy and size of the learned decision tree.

Language: Python - Size: 107 KB - Last synced at: 23 days ago - Pushed at: over 1 year ago - Stars: 5 - Forks: 0

BeataWereszczynska/SML_forged_banknotes

Comparison of numerous supervised machne 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)

Language: Jupyter Notebook - Size: 1.53 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

tdishant/Banknote-Authentication

Machine Learning / Data mining project in python. In this project, various classification algorithms such as Decision Tree, k-nearest neighbours, random forest and support vector machine have been implemented from scratch and have been applied on banknote authentication dataset. The goal of this project is to calculate and compare the accuracy of these algorithms in differentiating counterfeit bank notes from legitimate notes

Language: Jupyter Notebook - Size: 233 KB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 1