You can load cancer $-$ related datasets provided by the 'datasets' submodule in sklearn using

the following code

from sklearn.datasets import load$\_$breast$\_$cancer

raw$\_$data $=$ load$\_$breast$\_$cancer $0$

Apply three machine learning models, logistic regression, decision tree, and random forest,

and examine accuracy, precision, recall, F$1$ score, and ROC AUC score.

Choose one model from the results and plot ROC curves and precision $-$ recall curves.

Apply techniques, including grid search, to further improve performance for the selected

model. Examine accuracy, precision, recall, F$1$ score, and ROC AUC score after applying these

techniques and attempt to analyze the performance improvement.

Check the feature importance and analyze the results. GUYS DON't USE CHAT GPT$!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!$ I KNOW IF U GUYS USED CHAT GPT