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

My Little Green Book of Machine Learning and Deep Learning, Artificial Intelligence

Data pre-processing Turn Complex Data into Numbers Turn data into features. Turn data into feature vectors. Machine Learning models can...