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Jul 26th, 2017
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  1. using LightGBM
  2.  
  3. estim = LightGBM.LGBMMulticlass(num_iterations=0, num_class=3, learning_rate=0.000000001)
  4.  
  5. X = rand(1000,10);
  6. y = 1.0*(rand(1000) .> 0.5);
  7. y[1:3:end] = 2
  8.  
  9.  
  10. LightGBM.fit( estim, X, y; init_score = ones(3000), verbosity=10000)
  11. LightGBM.predict(estim, X)
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