Projects in Awesome Lists tagged with undersampling-technique
A curated list of projects in awesome lists tagged with undersampling-technique .
https://github.com/jesly-joji/money-laundering-classification
Money Laundering Classification on IBM Transactions
binary-classificaiton eda undersampling-technique xgboost-classifier
Last synced: 27 Nov 2025
https://github.com/mmsaki/credit-risks-ml
Using the imbalanced-learn and Scikit-learn libraries to build and evaluate machine learning models.
balanced-accuracy-scores classification-models credit-risk imbalanced-classification imbalanced-learning loan-prediction-analysis logistic-regression machine-learning oversampling predictive-modeling resampling sklearn smote-oversampler smoteenn-combination undersampling-technique
Last synced: 06 Apr 2025
https://github.com/demon-2-angel/cereberal-stroke-analysis
Cerebral stroke, a critical condition, demands vigilant analysis. Machine learning models, coupled with resampling techniques like SMOTEENN, enhance stroke prediction accuracy by addressing imbalanced datasets.
brain-stroke-analysis-and-classification cerebral machine-learning-algorithms oversampling-technique undersampling-technique
Last synced: 05 Oct 2025
https://github.com/sophy8281/sms-spam-detection
Spam messages detection model
classification data-exploration data-preprocessing data-visualization oversampling-technique undersampling-technique
Last synced: 07 Sep 2025
https://github.com/coderjolly/credit-risk-modelling
The aim of the project is to create a robust machine learning model that predicts the likelihood for a bank's customers to fail on their credit payments for the next month. The dataset used contains information on 24028 customers across 26 variables that includes information regarding whether customer defaulted, credit limits, bill history etc.
decision-tree-classifier machine-learning oversampling-technique pandas-processing undersampling-technique visualization
Last synced: 27 Jun 2025
https://github.com/soumyapro/credit-card-fraud-detection
The project was intended to detect fraudulent transactions from a highly imbalanced dataset.To solve the imbalance dataset problem random undersampling techniques were used.
Last synced: 01 Mar 2025
