Semi-supervised K-means++

1 Feb 2016Jordan YoderCarey E. Priebe

Traditionally, practitioners initialize the {\tt k-means} algorithm with centers chosen uniformly at random. Randomized initialization with uneven weights ({\tt k-means++}) has recently been used to improve the performance over this strategy in cost and run-time... (read more)

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