Attached Files:

• Athletes(1).ipynb (109.744 KB)

Zacharski Chapter 4 ( http://guidetodatamining.com/chapter4/.com )

Download the files (.txt) at the bottom of the page of chapter 4.

Data

athletesTrainingSet.txt

athletesTestSet.txt

irisTrainingSet.data

irisTestSet.data

mpgTrainingSet.txt

mpgTestSet.txt

Build a classification system using k-nearest neighbor approach (similar to the one presented in the book) using several cases:

1. ( case ) Normalize the data using Modified Standard Score
2. ( case ) Normalize the data using Z-score
3. ( case ) Normalize the data using Min - Max normalization on interval [ 0,1]
4. ( case ) Do not normalize the data

All of the functions that you need for this system are given inside the notebook Athletes.ipynb.

You will need to test how accurate your classification system is by running your model on the test sets ( Explanation in detail is given in the Zacharski Chapter4)

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