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LOF vs kNN

It is common to look first at the points with highest anomaly scores before taking any action. When several algorithms are used, the points with highest scores may differ.

In this final exercise, you'll calculate new LOF and kNN distance scores for the wine data, and print the highest scoring point for each.

This exercise is part of the course

Introduction to Anomaly Detection in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Scaled wine data
wine_scaled <- scale(wine)

# Calculate distance matrix
wine_nn <- 

# Append score column to data
wine$score_knn <-
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