Recitation 8: Hierarchical and k-means Clustering
author: Mitchell A. Peabody,
Massachusetts Institute of Technology, MIT
recorded by: Massachusetts Institute of Technology, MIT
published: Oct. 29, 2012, recorded: April 2011, views: 2191
released under terms of: Creative Commons Attribution Non-Commercial Share Alike (CC-BY-NC-SA)
recorded by: Massachusetts Institute of Technology, MIT
published: Oct. 29, 2012, recorded: April 2011, views: 2191
released under terms of: Creative Commons Attribution Non-Commercial Share Alike (CC-BY-NC-SA)
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Description
Topics covered: Unsupervised learning, k-means clustering, distance metric, cluster merging, centroid, k-mean error, hold out set, k value significance, features of k-means clustering, merits and disadvantages of types of clustering.
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