Practice
Practices
Air Pollution Regression Evaluation
You are given a dataset containing information about air pollution levels in different cities. Your task is to evaluate the performance of a regression model that predicts air pollution levels based on various factors such as population, industrial activity, and traffic. The dataset is as follows:
Dataset: Air Pollution Levels
| City | Population (thousands) | Industrial Activity Index | Traffic Index | Actual Pollution Level | Predicted Pollution Level |
|---|---|---|---|---|---|
| New York | 8173 | 0.87 | 0.78 | 45.2 | 44.8 |
| Los Angeles | 3981 | 0.65 | 0.91 | 55.6 | 56.2 |
| Chicago | 2716 | 0.56 | 0.72 | 38.9 | 39.4 |
| Houston | 2320 | 0.92 | 0.84 | 61.3 | 60.9 |
| Phoenix | 1684 | 0.74 | 0.68 | 48.7 | 48.3 |
| Philadelphia | 1584 | 0.58 | 0.75 | 41.5 | 42.1 |
| San Antonio | 1543 | 0.88 | 0.62 | 53.2 | 53.6 |
| San Diego | 1399 | 0.67 | 0.78 | 47.1 | 46.7 |
| Dallas | 1341 | 0.79 | 0.79 | 49.8 | 49.5 |
| San Jose | 1030 | 0.63 | 0.65 | 42.3 | 42.7 |
| Lagos | 14083 | 0.75 | 0.82 | 58.4 | 58.0 |
| Cairo | 10003 | 0.68 | 0.73 | 49.1 | 49.6 |
| Johannesburg | 9575 | 0.71 | 0.67 | 47.8 | 47.4 |
| Nairobi | 4397 | 0.53 | 0.75 | 35.6 | 36.1 |
| Casablanca | 3350 | 0.62 | 0.74 | 43.9 | 43.5 |
| Accra | 2298 | 0.49 | 0.68 | 33.4 | 33.9 |
Questions:
-
What is the dependent variable (target) in this regression problem?
- Population (thousands)
- Industrial Activity Index
- Traffic Index
- Actual Pollution Level
- Predicted Pollution Level
-
What are the independent variables (features) in this regression problem? (Select all that apply)
- Population (thousands)
- Industrial Activity Index
- Traffic Index
- Actual Pollution Level
- Predicted Pollution Level
-
Calculate the Mean Absolute Error (MAE) to evaluate the model's performance.
-
Calculate the Mean Squared Error (MSE) to evaluate the model's performance.
-
Calculate the Root Mean Squared Error (RMSE) to evaluate the model's performance.
-
Interpret the MAE value in the context of this regression problem.
Submission
You are required to submit documentation for practice exercises over the course of the term. Each one will count for 1/10 of your practice grade, or 2% of your overall grade.
- Practice exercises will be graded for completion not perfect correctness.
- You MUST supply the answers and upload your analysis as a single file to
Practice - Evaluationon Gradescope after the exercise to get the grade for this exercise.
Your log will count for credit as long as:
- It is accessible to your instructor, and
- It shows your own work.