Using Random undersampling, Tomeklinks, Random oversampling, SMOTE, SMOTE+Tomeklinks and ADASYN from inbuilt imbalanced learn library and found how many records added or discarded.
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Updated
Oct 21, 2024 - Jupyter Notebook
Using Random undersampling, Tomeklinks, Random oversampling, SMOTE, SMOTE+Tomeklinks and ADASYN from inbuilt imbalanced learn library and found how many records added or discarded.
CredVibe is an ML credit scorecard system achieving 95%+ default recall with explainable predictions for loan risk assessment. Features KS/Gini validation, Optuna tuning, FastAPI + Streamlit deployment. Generates CIBIL-like scores, and converts to business rules for BRE integration.
RTA severity predictor is an application which predicts the severity of road traffic accident, so as to pave the way for improving the safety level of road traffic.
Binary classification preprocessing benchmark for auto-insurance data: binning/discretization + Random UnderSampling & SMOTETomek + feature transformations/engineering + PCA dimensionality reduction + evaluation with Logistic Regression & Histogram Gradient Boosting 🚗
Credit card transactions fraud detection using classic algorithms
Classifying Travel Mode choice in the Netherlands using KNN, XGBoost, RF and TabNet
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