Write a program to perform supervised pattern classification using kNN classifiers as described in class. Your program should have two components: distance calculation and class assignment.

$1.$ Discuss whether you need to normalize the dataset or not. Check the ranges of values and that will give you a hint. Then, normalize the dataset.

$2.$ Separate the entire dataset $(613$ samples$)$ into training and testing set such as $70\%$ training, $30\%$ testing.

$3.$ For algorithm development, first implement a distance calculation module where a data set with labeled samples $($training data$)$ will be used to calculate distances to testing samples.

$4.$ Second implement an assignment module where it will find k$-$Nearest Neighbors to classify samples with unknown class assignment. You must implement these two modules in one program.

$5.$ Test your kNN for k$=1,3,5,7,$ and $9.$

$6.$ Show your testing results for different k values using their accuracy and confusion matrix.

Write a code in python language