Answer the questions below using Python Coding in Jupyter.

CS 250 01 Fall 2022
Homework Assignment 4
Due on Moodle: Before class on Wednesday, October 05. Mail submissions will not be
accepted. Submit one single Jupyter Notebook for all questions. For this homework
assignment, download the Possum Regression dataset from Kaggle(Link:
https://www.kaggle.com/datasets/abrambeyer/openintro-possum) and do the following:
1.
a. Read the data into a dataframe
[1 points]
b. Find if there are any cells containing null values, and remove those rows.
c. Drop the ‘case’, ‘site’ and ‘Pop’ columns.
[2 points]
[2 points]
d. Separate the sex column into a separate array/dataframe/series called labels,
and the rest of the remaining columns into an array/ dataframe called features.
Remember to drop the original sex column from here
[5 points]
2. Now do the following:
a. Split the features and labels into 75% training and 25% testing using
train_test_split()
[5 points]
b. Predict the label (m or f) of each test data based on the K-nearest-neighbor
technique. Use a value of K>1 and either Euclidean or Manhattan distance.
[5 points]
3. Evaluate the performance on the test data using normalized confusion matrix (code
given in class)
[5 points]