Read more about Banks could strengthen credit card fraud screening with ensemble machine learning model on Devdiscourse ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the AdaBoost.R2 algorithm for regression problems (where the goal is to predict a single numeric value). The ...

Computational: We take random inputs, follow complex steps, and hope the output makes sense. And then blog about it.

Dr. James McCaffrey from Microsoft Research presents a C# program that illustrates using the AdaBoost algorithm to perform binary classification for spam detection. Compared to other classification ...

Abstract: Credit card fraud detection is a critical problem for any credit card issuing banks. The AdaBoost classifier is used in this study to identify fraudulent transactions. By comparing the ...

This repository includes the scripts to replicate the results of my WORKING paper entitled "A Machine Learning Approach to Detect Accounting Frauds".

We develop an adaptive machine-learning framework that addresses cross-operation-condition battery lifetime prediction, particularly under extreme conditions. This framework uses correlation alignment ...

This project has the aim to analyze the Heart Disease dataset to build a classifiers to predict whether people have heart disease or not.

ABSTRACT: Cardiovascular disease (CVD) risk assessment is an important instrument to enhance the clinical decision in the daily practice as well as to improve the preventive health care promoting the ...