Mouneshgouda/Insurance-claim

Prediction of Auto Insurance Claim detection • Problem statement is related is to insurance domain • Performed a key role in Machine learning : Data gathering, cleaning ,Feature engineering ,Feature Selection ,Data visualization Model building ,Hyper parameter tunning • It’s a Classification problem evaluated model using confusion matrix and model

14
/ 100
Experimental

The project employs an autoencoder deep learning architecture to enhance classification performance beyond traditional ML approaches, leveraging dimensionality reduction for improved feature representation. Model evaluation combines confusion matrix analysis with AUC-ROC curves to assess both classification accuracy and threshold-independent performance. The implementation spans the complete ML pipeline from raw insurance claim data through hyperparameter optimization to final model validation.

No commits in the last 6 months.

No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 0 / 25

How are scores calculated?

Stars

24

Forks

Language

Jupyter Notebook

License

Last pushed

Dec 31, 2022

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Mouneshgouda/Insurance-claim"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.