This handbook uses the classic Breast Cancer detection dataset. It is one of the first projects I had my hands-on experience to handle a Data Science problem. It is a binary class classification problem to predict if the patient has cancer or not. The dataset uses 10 features of the cell nucleus for this analysis. This handbook also explains how to interpret results and which result parameter best suits the context (here Predicting the Cancer correctly). Interesting things to find in this handbook are the usage of GridSearch for hyperparameter tuning and ROC/AUC curves for evaluating model performance.
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This handbook uses the classic Breast Cancer detection dataset. It is a binary class classification problem to predict if the patient has cancer or not. The dataset uses 10 features of the cell nucleus for this analysis. This handbook also explains how to interpret results and which result parameter best suits the context (here Predicting the Ca…
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This handbook uses the classic Breast Cancer detection dataset. It is a binary class classification problem to predict if the patient has cancer or not. The dataset uses 10 features of the cell nucleus for this analysis. This handbook also explains how to interpret results and which result parameter best suits the context (here Predicting the Ca…
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