Welcome and Introduction

Supervised Learning in R: Regression

Nina Zumel and John Mount

Data Scientists, Win Vector LLC

What is Regression?

Regression: Predict a numerical outcome ("dependent variable") from a set of inputs ("independent variables").

  • Statistical Sense: Predicting the expected value of the outcome.
  • Casual Sense: Predicting a numerical outcome, rather than a discrete one.
Supervised Learning in R: Regression

What is Regression?

  • How many units will we sell? (Regression)
  • Will this customer buy our product (yes/no)? (Classification)
  • What price will the customer pay for our product? (Regression)
Supervised Learning in R: Regression

Example: Predict Temperature from Chirp Rate

Supervised Learning in R: Regression

Predict Temperature from Chirp Rate

Supervised Learning in R: Regression

Predict Temperature from Chirp Rate

Supervised Learning in R: Regression

Regression from a Machine Learning Perspective

  • Scientific mindset: Modeling to understand the data generation process
    • Engineering mindset: *Modeling to predict accurately

Machine Learning: Engineering mindset

Supervised Learning in R: Regression

Let's practice!

Supervised Learning in R: Regression

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