Description
Your task is to predict whether a patient has heart disease or not. You can download and see information about data by following this link. You should do the following steps in your homework:
- Keep 20 percent of the data for testing.
- Do logistic regression and try to find the best hyperparameters (using sklearn).
- Normalize your data using standard normalization and then repeat the previous step.
- Try to find the best neural net to solve this problem which will have no more than 2 hidden layers (use sklearn).
- Normalize your data using standard normalization and then repeat the previous step. f*) Do the step d) using keras.
- g) Compare accuracies of all obtained models.
Remarks:
- You will not get a full grade, if you don’t have more than 85% accuracy on the test dataset in at least one of the steps above.
- Exercises with asterisks are supplementary and will not be graded.
- Don’t forget about train, validation and test sets.
- Use jupyter notebook for writing your code.
- You can use google for any question, but don’t do copies of others’ codes.
- You can ask me whatever you want and whenever you want.
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