What type of data is best suited for hierarchical clustering?

Practice Questions

Q1
What type of data is best suited for hierarchical clustering?
  1. Large datasets with millions of points
  2. Data with a clear number of clusters
  3. Data where relationships between clusters are important
  4. Data that is linearly separable

Questions & Step-by-Step Solutions

What type of data is best suited for hierarchical clustering?
  • Step 1: Understand what hierarchical clustering is. It is a method of grouping data points into clusters based on their similarities.
  • Step 2: Identify the type of data that has meaningful relationships. This means the data should show how different groups are related to each other.
  • Step 3: Look for data that can be represented in a way that shows these relationships, such as distances or similarities between data points.
  • Step 4: Consider data types like numerical data, categorical data, or even text data that can be converted into numerical form.
  • Step 5: Ensure that the data has enough observations to form meaningful clusters.
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