What are some common outlier detection algorithms?
Some common outlier detection algorithms include Z-Score, Isolation Forest, and DBSCAN. Would you like to know more about any specific one?
Can you explain how the Isolation Forest algorithm works?
Sure! Isolation Forest works by randomly selecting a feature and a split value, isolating observations. Outliers are easier to isolate, resulting in shorter paths in the tree.
What are the advantages of using DBSCAN for outlier detection?
DBSCAN is great for detecting outliers in clusters of varying shapes and sizes. It doesn't require specifying the number of clusters in advance, which is a big advantage!
Are there any limitations to these algorithms?
Yes, each algorithm has its limitations. For example, Z-Score assumes a normal distribution, which may not always be the case. Isolation Forest can struggle with high-dimensional data.
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