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
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.
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Dec 31, 2022
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