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Material Detail

Recitation 8: Hierarchical and k-means Clustering

Recitation 8: Hierarchical and k-means Clustering

This video was recorded at 6.00SC Introduction to Computer Science and Programming, Spring 2011 . 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.
Keywords:
videolectures, ocwc, oec
Disciplines:
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More about this material

Material Type:
Presentation
Date Added to MERLOT:
February 10, 2015
Date Modified in MERLOT:
February 10, 2015
Author:
Submitter:
The Open Education Consortium
Primary Audience:
College General Ed, College Lower Division, College Upper Division
Technical Format:
Video
Mobile Compatibility:
Not specified at this time
Language:
English
Cost Involved:
No
Source Code Available:
No
Accessibility Information Available:
Unknown
Creative Commons:
Creative Commons License
This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States

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