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
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Updated
Mar 18, 2022 - Jupyter Notebook