learn-co-students / ds-skills-midterm-london-ds-091018

Midterm Project

The midterm project is due on class 10. You will have class 9 to continue to work on it, but it is a good idea to continue working on it. Your final submission should include a written description of your process from preprocessing through model evaluation. As a reminder of general requirements and key areas to include, refer to the midterm rubric below.

Regression Outline Reminder

As a reminder, here is our general outline for regression :

• Define X and y
  • y should be a continuous numeric variable
  • X should be a number of numeric features *X features may need substantial preproccesing including: * Transforming datetime values * Normalizing features ranges/distributions * Creating dummy variables * Ensuring there are no categorical variables coded (misleadingly) as numbers
• Train / Test Split
• Fit algorithm on training data
  • Cross Validation
  • Feature Engineering
    • Synthetic Polynomial Features / Polynomial Regression
• Evaluate Model Performance on Test Set
  • Repeat process with seperate train/test split; do results hold?
• Continue feature engineering, tuning, etc.