Unsupervised Learning

This covers unsupervised learning topics like k-means clustering and association rules

European Employment Data – Clustering

The data are the percentage employed in different industries in Europe countries during 1979. The purpose of examining this data is to get insight into patterns of employment (if any) amongst European countries in 1970s.

Variable Names:

1. Country: Name of country
2. Agr: Percentage employed in agriculture
3. Min: Percentage employed in mining
4. Man: Percentage employed in manufacturing
5. PS: Percentage employed in power supply industries
6. Con: Percentage employed in construction
7. SI: Percentage employed in service industries
8. Fin: Percentage employed in finance
9. SPS: Percentage employed in social and personal services
10. TC: Percentage employed in transport and communications

Cincinnati Zoo Data – Association Rules

The food association data contains 19076 observations with 118 variables. A set of rules are developed on most frequently sold items.