Welcome to the course!

Unsupervised Learning in R

Hank Roark

Senior Data Scientist at Boeing

Chapter 1 overview

• Unsupervised learning
• Three major types of machine learning
• Execute one type of unsupervised learning using R

Types of machine learning

• Unsupervised learning
  • Finding structure in unlabeled data
• Supervised learning
  • Making predictions based on labeled data
  • Predictions like regression or classification
• Reinforcement learning

Labeled vs. unlabeled data

¹ Sample from Murphy, Machine Learning: A Probabilistic Perspective

Labeled vs. unlabeled data

¹ Sample from Murphy, Machine Learning: A Probabilistic Perspective

Unsupervised learning - clustering

• Finding homogeneous subgroups within larger group

People have features such as income, education attainment, and gender

Unsupervised learning - clustering

• Finding homogeneous subgroups within larger group

$$

Unsupervised learning - clustering

• Finding homogeneous subgroups within larger group

Clustering

Clustering examples

$$

Clustering examples

$$

Unsupervised learning - dimensionality reduction

• Finding homogeneous subgroups within larger group
  • Clustering
• Finding patterns in the features of the data
  • Dimensionality reduction

Unsupervised learning - dimensionality reduction

• Find patterns in the features of the data
• Visualization of high dimensional data
• Pre-processing before supervised learning

Challenges and benefits

• No single goal of analysis
• Requires more creativity
• Much more unlabeled data available than cleanly labeled data

Let's practice!

Unsupervised Learning in R