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4 cards from this section. Quick, good the night before a test.
What is clustering?
Think about organizing items by shared characteristics.
Name one advantage of K-Means clustering.
What do we want a clustering method to be?
What is the main goal of clustering?
What is the purpose of clustering in machine learning?
True or False: DBSCAN requires you to predefine the number of clusters.
Think about how DBSCAN groups data points.
Suppose you apply K-Means clustering on a dataset and received poor results due to sensitivity to outliers. What approaches can you take to mitigate this issue?
Think about how data transformations can affect clustering.
A manager wants to use DBSCAN but is unsure of how to set its parameters. What general advice would you give to help them choose optimal values for eps and minPts?
Consider the density of clusters when adjusting these parameters.
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