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qda-a435

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srinidhi14vaddy / Breast-Cancer-Wisconsin-Anomaly-Diagnosis

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Performed statistical-EDA and normalization analysis on digitized mass images with 10 nuclei features (radius, texture) Predicted malignant - benign cancer using Logistic, LDA-QDA, KNN, Lasso-Ridge classifiers with 0.89, 0.88, 0.92, 0.96 and 0.97 accuracies respectively along with decision boundaries and ROC curves

machine-learning exploratory-data-analysis eda statistical-analysis logistic-regression breast-cancer-prediction lda ridge-regression breast-cancer-wisconsin normalization lasso-regression classification-algorithims knn-classifier discriminant-analysis qda-a435
  • Updated Mar 18, 2022
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