MLF Capstone Feedback

[mackenzieyoung]

Rubric Score

Criteria 1: Valid Python Code

• Score Level: 4 (Exceeds expectations)
• Comment(s): Great job, your code runs without any errors.

Criteria 2: Exploration of Data

• Score Level: 3 (Meets expectations)
• Comment(s): You're off to a good start with your exploratory analysis. Good job recognizing that many of the income values were -1 (i.e., not reported), and dealing with those data points. I would be careful with your body_type mapping, since the values you chose are quite arbitrary. It seems like you might have chosen increasing values with increasing 'fitness', but this is very subjective, which will make interpreting the results difficult. Ideally, your exploratory analysis would inform your research questions to a greater extent (for example, by looking at relationships between variables you're interested in), but it is good that you motivated your research question with some background info.

Criteria 3: Machine Learning Techniques used correctly

• Score Level: 3 (Meets expectations)
• Comment(s): Good job overall with your choice of machine learning algorithms. It would have been better if you had left income as-is for your regression analysis, instead of using the income mapping. I'm not sure that it would have resulted in better predictions, but it would make interpreting your results easier. Also, it would have been better if you had looked at performance measures other than accuracy for your classification models (like F1 score), but good job looking at R^2 for your regression models.

Criteria 4: Report: Are conclusions clear and supported by data?

• Score Level: 3 (Meets expectations)
• Comment(s): Nice job laying out your research questions and formatting your presentation. One thing missing from your analysis is a discussion of which features are able to predict higher incomes. For all we know, it could be that 'less attractive' people learn more in your data. One way to look at this is to look at the coefficients of your regression model results (although your regression models didn't perform very well...).

Criteria 5: Code formatting

• Score Level: 4 (Exceeds expectations)
• Comment(s): Nice job, your code is clean and formatted well. Good job using comments to break your code up into sections.

Overall Score: 17/20