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ProgNeo

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Oct 6th, 2022
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Python 0.34 KB | None | 0 0
  1. net.fit(X_test, shuffle=True)
  2. Y_test_predict = net.predict(X_test)
  3.  
  4. res_df = pd.DataFrame(X_test)
  5. res_df['Class'] = Y_test_predict
  6. df_weights = pd.DataFrame(net.weights)
  7. fig = go.Figure(data=[
  8.     go.Scatter3d(
  9.         x=res_df[0], y=res_df[1], z=res_df[2], mode='markers', marker=dict(size=4, color=res_df.Class)
  10.         )
  11.     ])
  12. fig.show()
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