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Socially Relevant Project (SRP). Using the UCI breast cancer dataset to analyze and build a model with high accuracy, precision and recall. This could be used to predict whether a patient has a malignant or benign tumor based on the 10 different FNA cell parameters.

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Roshni-Bala/Breast-Cancer-Risk-Prediction

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Breast-Cancer-Risk-Prediction

Socially Relevant Project (SRP) - Semester VI - IT, Anna University
Using the UCI breast cancer dataset to analyze and build a model with high accuracy, precision and recall.
This could be used to predict whether a patient has a malignant or benign tumor based on the 10 different FNA cell parameters.

Estimators used = Logistic Regression, Naive Bayes Classifier, KNN, Random Forest Classifier
Final Estimator used = Support Vector Classifier

View Deployment

Streamlit Deployment:
https://roshni-bala-breast-cancer-risk-predictio-risk-predwebapp-4pzyjh.streamlitapp.com/

Heroku Cloud Deployment:
https://srp-webapp.herokuapp.com/
^ Heroku to stop free tier services from November, 2022

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Socially Relevant Project (SRP). Using the UCI breast cancer dataset to analyze and build a model with high accuracy, precision and recall. This could be used to predict whether a patient has a malignant or benign tumor based on the 10 different FNA cell parameters.

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