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      1 # Stacking
      2 
      3 ML D5
      4 
      5 **Definition:** Stacking is the idea that we should create a dedicated model to act as a voting machine for an ensemble of predictive models.  
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      7 This is in contrast with soft and hard voting which does simple calculations to determine the output based on inputs from the outputs of predictors (I know lots of words).
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      9 This models that does the final prediction is called a blender or meta learner and through the process of blending gives and output.
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     11 A good way to do this is by training the model on the outputs of out of sample data for all prior models.