[MINI] The Elbow Method

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.

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This episode was published on March 18, 2016.

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