Data Mining Project     By using the above datasets ( [Pima Indians Diabetes Dataset](https://archive.ics.uci.edu/ml/datasets/pima+indians+diabetes) ) calculate and compare the accuracy between KNN...

Data Mining Project

  By using the above datasets ( Pima Indians Diabetes Dataset ) calculate and compare the accuracy between KNN Accuracy and 10-fold Cross-validation with Logistic Regression.

Solve the following cases before calculating the accuracy.

• Import the sklearn library for all the datasets.

• Read the data for all the datasets and normalize them.

• Define the predictions and print them for all datasets.

• Create a classifier to search for an optimal value of K for KNN Algorithm for cross-validation accuracy.

• Plot the value of K for KNN Versus the cross-validation accuracy.

• Print out the KNN accuracy and 10-fold cross-validation with logistic regression and compare them.

All of the functions that you need for this system are given inside the notebook Cross-validation.ipynb in Module 7 of your class sessions.

You will need to test how accurate your classification system is by running your model on the test sets

You should submit / upload one IPython Notebook  file ( .ipynb )