Sveriges mest populära poddar

Data Skeptic

[MINI] The Elbow Method

15 min • 18 mars 2016

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.

Förekommer på
00:00 -00:00