UoFT-DSI | LCR - Assignment 1

[akorade]

Filled in code cells with answers and executed them, including data exploration, standardization, train/test split, and KNN hyperparameter tuning. Added outputs and explanations for each step, updated kernel metadata, and fixed minor issues in code execution.

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

Completed Assignment 1 on KNN Classification with the Wine dataset. Changes include:

• Data inspection code (rows, columns, variable types, predictor count)
• Data preprocessing (standardization and train-test split)
• Grid search implementation for hyperparameter tuning using 10-fold cross-validation
• Model evaluation on test set using the optimal n_neighbors value

What did you learn from the changes you have made?

• How to standardize features using StandardScaler and why it's critical for KNN (features must be on the same scale for distance calculations)
• The difference between predictor variables (continuous features) and response variables (categorical labels)
• How train_test_split() creates non-overlapping training and testing sets
• How GridSearchCV automates hyperparameter tuning by testing multiple values with cross-validation
• The importance of setting random seeds for reproducible results

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

NA

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

NA

How were these changes tested?

I tested all changes locally using Jupyter Notebook in Visual Studio Code

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

NA

Checklist

• I can confirm that my changes are working as intended

[PatelVishakh]

Assignment 1: Incomplete. Needs a few changes.
Required Changes:

Q1)III) The type of variable is categorical. In a data science setting, this question is asking whether the variable is continuous or categorial(integer, ordinal are other options).
Q4) Missing answer

[PatelVishakh]

Assignment 1: Pending resubmission. Needs a few changes.
Required Changes:

Q1)III) The type of variable is categorical. In a data science setting, this question is asking whether the variable is continuous or categorial(integer, ordinal are other options).
Q4) Missing answer

[akorade]

Assignment 1: Pending resubmission. Needs a few changes.

Required Changes:

Q1)III) The type of variable is categorical. In a data science setting, this question is asking whether the variable is continuous or categorial(integer, ordinal are other options).

Q4) Missing answer

Hi Vishakh ,
I am travelling to my family due to emergency. I did resubmit my assignment. I see that it got submitted through my friends account by mistake as I was using his laptop

[PatelVishakh]

Assignment 1 Pending resubmission.

Q&A) section complete.

Q4) Output is still missing.

[akorade]

@PatelVishakh Please review the updated output for assignment 1. Following are the changes

1. Added Q4 output
2. Q3, iii output now prints variable type

[PatelVishakh]

Assignment 1 Complete. Good Edits.