committing assignment 1

[thomasdudgeon]

What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)

Adding code to explore the data, answer questions, and run a best-fit KNN

What did you learn from the changes you have made?

How to run a KNN using Python

Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?

I know how to do this method in R but it was fun to learn the method in another program

Were there any challenges? If so, what issue(s) did you face? How did you overcome it?

The main challenge was learning formatting differences, since R and Python are so close I was frequently having syntax issues

How were these changes tested?

Repetition

A reference to a related issue in your repository (if applicable)

Checklist

• I can confirm that my changes are working as intended

[PatelVishakh]

Assignment 1:Complete. Great work! Suggested Changes:


When answering questions rather then commenting in after manually reading the output, should automate it. for eg.

Number of observations (rows)
num_observations = wine_df.shape[0]
print(f"Number of observations: {num_observations}")

Q1)III) The type of variable is categorical. In a data science setting, this question is asking whether the variable is numerical or categorial (Integer, continuous, ordinal are for distinguishing further) to assess whether classification or regression methods should be used. The complete statement should Class is a Categorical Variable, represented here in integers (0,1,2) stored in our Dataframe as int64.

Q2)II) We do not standardize the response variable Class not because it is categorical variable, but rather because that is the quantity of interest and we would have to rescale our predictions for them to be interpretable.

Vishakh Patel [LS]