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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

Machine Learning Workflow

Data cleaning Missing data Outlier Others: duplicates, typos, special characters Strategy for missing data: imputation, mean, median...