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← Compression While Preserving Information - Intro to Machine Learning

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Showing Revision 3 created 05/24/2016 by Udacity Robot.

  1. And SelectkBest is probably going to be the right answer here,
  2. because you know exactly how many you're expecting to get out.
  3. You're expecting to get exactly two, so
  4. it will throw away all the features except the two that are the most powerful.
  5. Select Percentile isn't a great choice for this scenario,
  6. because you don't already know exactly how many features you have.
  7. Although in the case that we gave in the warm up example,
  8. where you have exactly four features and you know you want two, you could
  9. also just run Select Percentile with 50%, and that will give you two features.