assignment-1

[Yutong2002]

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

Based on the given dataset, I provided the overview of the dataframe (e.g. identity of variables, row & column numbers); pretreated the dataframe (including standarization and training & testing dataset spliting); Computed & optimized KNN model based on the cleaned dataframe, including generate KNN model based on training data pattern, performed cross-validation to validate the optimal selection of number of neighboring K, and eventually, test the evaluation accuracy of the computed KNN model using testing dataset.

What did you learn from the changes you have made?

I revised how to constract KNN model building and make prediction using the model starting from the raw data.

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

At the step of split the data into a training and testing set, I was thinking to import wine_df (excluded 'class') as the X value. However, I used standarized dataframe instead, since the data has to be standarized before using for computation.

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

N/A

How were these changes tested?

All the scripts were ran in the Jupyter Notebook on VS code; Correct results were generated as results.

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

N/A

Checklist

• [ x ] I can confirm that my changes are working as intended