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ncoudray / DeepPATH

Classification of Lung cancer slide images using deep-learning
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Set mode '1_sigmoid' for classification of Normal, LUAD, LUSC? #19

Closed hongyiyu closed 5 years ago

hongyiyu commented 6 years ago

  1. If I want to training to classify Normal, LUAD, LUSC, do I need to set the training mode to '1_sigmoid'?

  2. In the abstract of the paper. It states that average area under the curve (AUC) of 0.97 for classifying Normal, LUAD, LUSC. I want to know how you calculate AUC for multi-classification task, as I know AUC is for binary classification. Is it like that calculate for following three AUC and average them? (1) Normal vs LUAD and LUSC, (2) LUAD vs Normal and LUSC, (3) LUSC vs Normal and LUAD.

  3. Why just simply applying softmax and select max prediction score for per-tile like most of classification task. Is there any other reason for using sigmoid for each output class?

ncoudray commented 6 years ago

Hi -

  1. No, we use 0_softmax.
  2. Correct. As described in https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html
  3. See (1) . We do use softmax for that classification task.

HTH N.