CSS 300 Module 5 Activity Worksheet

Use this worksheet to complete your lab activity. Submit it to the applicable assignment

submission folder when complete.

Deliverable:

– A word document answering the following questions

Using the Weather.csv dataset from Module 4

Part 1: Metrics for Evaluation

1. Calculate the following metrics: mean absolute error, mean squared error, root mean

squared error, and the R2 score. Use the following code samples:

print(‘Mean Absolute Error:’, metrics.mean_absolute_error(y_test,

y_pred))

print(‘Mean Squared Error:’, metrics.mean_squared_error(y_test,

y_pred))

print(‘Root Mean Squared Error:’,

np.sqrt(metrics.mean_squared_error(y_test, y_pred)))

print(‘R-squared Score:’, regressor.score(X, y))

Part 2: Model Refinement

1. Rerun the linear regression model from Module 4, but change the percentage of records

that are used for testing. Try using 0.25 and 0.3.

2. Calculate the same metrics from above.

3. Use a scatter plot to visualize all three models.

4. Evaluate the three models. Are any of them underfit or overfit? Which % of testing data

performed best?