Subject
4 entries
K Means
Bookmarks
Visualizing K-Means Clustering
Naftali Harris's interactive visualization of k-means clustering — place points on a canvas and watch the algorithm converge step by step. Exposes why initialization matters and where k-means fails.
How a Math Genius Hacked OkCupid to Find True Love
Chris McKinlay scraped OkCupid, clustered female users with k-means, and optimized his profile to score high compatibility across all clusters — then met his wife through the resulting message flood. A crowd-pleasing 2014 story about data science applied to dating.
The Remarkable k-means++
Larry Wasserman's Normal Deviate blog post on k-means++ — the 2007 initialization trick from Arthur and Vassilvitskii that gives k-means an O(log k) approximation guarantee and better convergence in practice.
K-Means Clustering 86 Single Malt Scotch Whiskies
Clustering 86 single malt Scotch whiskies by flavor profile using k-means in R — a fun worked example that makes clustering tangible. Shows how to choose k and interpret results when the data has real-world meaning.