Found 59 repositories(showing 30)
sscswapnil
Business Problem: Credit card fraud detection using supervise ML Model/Algorithm in R language
Credit Card Fraud Detection using traditional Machine Learning Techniques (Random Forest with Python Scikit-Learn)
diwashrestha
A credit card fraud detection system made with h2o and R.
udurgesh6
In this project I have built a machine learning model with SMOTE to identify the fraudulent cases. I have also went through random over sampling and random under sampling to see how the model works.
No description available
Bayodecode
Credit Card Fraud Detection with Machine Learning in R
shauryatiwari1
this is an app with python and flask along with ML algorithms that detects if any transaction is fraud
An algorithm that can detect fradulent transactions after training with data extracted from Kaggle
All My projects
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Detection of fraud activity in a credit card transaction using random forest algorithm. Parallelized the random forest to make it more faster and efficient for detecting the fraud activity much quicker for real time application.
ajaychouhan-nitbhopal
This is a XGboost classifier model for Credit Card Fraud Detection on Anonymized features dataset of 284,807 transactions. Hyperparameters of the models are tuned with GridSearchCV and RandomizedSearchCV and Comparison is also done between them.
ankitanshumanmohapatra
Here I deployment of a credit card fraud detection system using ML & DL models- LR, ANN, GMB & Decision Tree to predict fraudulent transactions with high precision & recall using R-Programming.
EconMike
Showing how to create at supervised learning model (Classification) and comparing that with a neural network model using the same dataset. Please find the Credit Card dataset on the Kaggle website. Keywords: neural-networks, ML, r-programming, ggplot2, Fraud detection. Data visualizations
OzlemGulsumKilickaya
Credit Card Fraud Detection with R
sksdotsauravs-beuth
No description available
Machine Learning Classification Model with R and Kaggle Credit Card Fraud Data
abhinav-deep
Credit card fraud detection using Machine Learning with R.
kundankumar-35
"This project involves building and evaluating a machine learning model, specifically Logistic Regression, to detect fraudulent credit card transactions. A key focus was on addressing the challenge of a highly imbalanced dataset through techniques like undersampling to improve the model's ability to identify rare fraudulent activities."
abderrazakmahiii
A machine learning project for detecting credit card fraud using the Kaggle 2023 dataset. Includes data preprocessing, Random Forest training with cross-validation, model evaluation (ROC, confusion matrix), and feature importance analysis.
Build a machine learning model to predict the possibility of a Heart Disease diagnosed in a patient, given you have a set of information about the patient (Age, Sex, ChestPainType, RestingBP, Cholesterol, FastingBS, RestingECG, MaxHR, ExerciseAngina, Oldpeak and ST_Slope), using all of the machine learning algorithms taught to you during your training at Acmegrade Internship. And find out the best suited model for the given dataset
This project implementations a fraud detection system for credit card transactions using a Random Forest Classifier.
It is an advanced fraud detection model with XGBoost & SMOTE
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Achina-Y-Ofori-Aboagye
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