Chapter 5. Clustering and Other Unsupervised Learning Methods
In this chapter, we will:
Define machine learning
Introduce unsupervised and supervised methods
Focus on K-means, a classic machine learning algorithm, in detail
We'll use K-means to improve the application we created in Chapter 4, Creating Your First Qlik Sense Application. In Chapter 4, Creating Your First Qlik Sense Application, we created a Qlik Sense application to understand our customers' behavior. In this chapter, we'll create clusters of customers based on their annual money spent. This will give us a new insight. Being able to group our customers based on their annual money spent will allow us to see the profitability of each customer group and deliver more profitable marketing campaigns or create tailored discounts.
Finally, we'll see hierarchical clustering, different clustering methods, and association rules. Association rules are generally used for market basket analysis.
