Shikun commited on
Commit
a701353
·
1 Parent(s): 90a3d3e

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +2 -0
app.py CHANGED
@@ -124,10 +124,12 @@ if file_upload is not None:
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  with open("automl4.pkl", "rb") as f:
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  model = pickle.load(f)
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  predictions = model.predict(column)
 
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  #pred_clip = np.clip(pred_clip, [0.2,0.4,3.9,0.2,13.9,13.8,13.2],[1.01,1.21,4.71,0.8,14.701,14.201,14.001])
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  #predictions = pd.DataFrame(pred_clip.tolist(), columns = ["w1","w2","w3","s1","l1","l2","l3"])
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  r2_score = r2_score(best_column, predictions)
 
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  if r2_score < 0.98:
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  predictions = perturb_array(best_column)
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  predictions = pd.DataFrame(predictions, columns = ["w1","w2","w3","s1","l1","l2","l3"])
 
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  with open("automl4.pkl", "rb") as f:
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  model = pickle.load(f)
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  predictions = model.predict(column)
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+ st.write(predictions)
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  #pred_clip = np.clip(pred_clip, [0.2,0.4,3.9,0.2,13.9,13.8,13.2],[1.01,1.21,4.71,0.8,14.701,14.201,14.001])
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  #predictions = pd.DataFrame(pred_clip.tolist(), columns = ["w1","w2","w3","s1","l1","l2","l3"])
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  r2_score = r2_score(best_column, predictions)
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+ st.write(r2_score)
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  if r2_score < 0.98:
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  predictions = perturb_array(best_column)
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  predictions = pd.DataFrame(predictions, columns = ["w1","w2","w3","s1","l1","l2","l3"])