![[MINI] The Elbow Method](https://static.libsyn.com/p/assets/b/0/a/3/b0a3557201505296/elbow-method.png)
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Show Notes
Certain data mining algorithms (including k-means clustering and k-nearest neighbors) require a user defined parameter k. A user of these algorithms is required to select this value, which raises the questions: what is the "best" value of k that one should select to solve their problem?
This mini-episode explores the appropriate value of k to use when trying to estimate the cost of a house in Los Angeles based on the closests sales in it's area.