Wednesday, April 12, 2017

K mean clustering sklearn best practice - Udacity Machine Learning Nanodegree Unsupervised Learning

There are three key k means clustering parameters in sklearn that you will need to pay attention to:

  • Number of centroids, aka center of clusters, initialized
  • Max number of iterations, used to optimize the algorithm. Best practice recommended by Udacity is 300
  • Number of different iterations, with initialization of centroids

Understand the Softmax Function in Minutes

Reposted from Uniqtech's Medium publication with permission. This is retrieved on May 14 2019. Uniqtech may have a newer version. Unde...