4 ms·

Strange to see dimensionality reduction as the root node? I’m having a hard time reading this diagram.

• rsrsrs86 5y ago
  Presenting dimensionality reduction as the starting point in machine learning is not usual, but it does make sense, technically. A classification model can be seen as mapping inputs from an N dimensional space to set of labels. Regression maps N dimensional spaces to the real line and so on. Even a sample mean reduces a set with dimensionality equal to the sample size to a single real number.
  • jrumbut 5y ago
    You're right but really the sheet is just a mess. Naive Bayes is on both sides of "Data Too Large" and the wrong side of "Explainable." It's almost like they put some algorithm names and machine learning concepts in a hat and drew them at random.