4th Place Solution

Credit card fraud detection using machine learning techniques

Fraud analysis and detection.

The methods and results of the publication "Potential COVID-19 test fraud detection: Findings from a pilot study comparing conventional and statistical approaches" are described in more detail in this appendix. The R-syntax for the calculation is provided, as well as a pseudo data set with which the syntax can also be tested.

Fraudulent websites detector built with nonparametric models

A Wald statistic for group-level cheating detection

The Wirecard scandal is considered one of the largest financial scandals of the decade, which caused losses of several billion euros. This analysis examines the digit structure of Wirecard's financial figures in the period from 2005 to 2019 by analyzing the conformity with the expected frequency distributions according to Benford's law. The resu…

Built LDA and QDA models on variables obtained from Principal Component Analysis (PCA) and Kolmogorov-Smirnov (KS) and tuned by leave-one-out cross-validation (LOOCV) to predict fraudulent online advertising click traffic

HarvardX Data Science Certificate: Choose Your Own Project

Script to predict fraud clicks in ads.

Outlier Detection Using Cluster Analysis

The aim of this project is to build a classifier that can detect credit card fraudulent transactions. I used a variety of machine learning algorithms like Decision Trees, Logistic Regression, Artificial Neural Networks and finally, Gradient Boosting Classifier

The repository contains implementations of different univariate outlier detection algorithms

Human or Robot? Predict if an online bid is made by a machine or a human.

A program based on semi-supervised learning to detect CerditCard Fraud Detection on Very Unbalanced database

Big Data Analytics course work at Harper College: Proof of concept - Fraud Detection

h2o is a ML library that can be used with R and Python. Here are some R examples for supervised and unsupervised methods.

This is an UPDATED deep statistical data analysis of the 2020 Presidential Race at the federal, state, and local county level. Benford's Law analysis was conducted at each level to detect for ballot fraud and manipulation.