Predicting probabilities with H2O flow

0
votes

Is it possible to predict probabilities in a binary classification task a in H2O flow? In particular I am finding difficulties in camputing the probability instead a crisp prediction because I can't see option in the UI of H2O when predicting.

If it's not possible doing it in H2O Flow, is there a way to do it in R (or Python) using the same model built in H2O flow?

Thanks in advance for any help.

1
h2o
Could you give a more specific example and what you tried? - Jones1220
I've imported the dataset in H2O flow then I've run a deep learning algorithm on a classification task and at the end I've clicked 'predict' in the the model options but unfortunately I didn't find an option to predict probabilities, just crisp. - Luca Pedretti

1 Answers

0
votes

This is possible in Flow and it is also possible to get the model from the backend using its key and then continue with your model analysis in one of the apis (R/Py)

Please also take a look at the documentation on how to make predictions in Flow if needed. After you build a model you will see that there is a predict button:

  1. Click on the predict button.
  2. Specify a name for your prediction frame, the model will already be set, select the frame you want to predict on using the frame dropdown menu, and then click on the action button called predict.
  3. In the next cell called Prediction you will see a table that will have three hyperlinks (model, frame, and predictions). The third hyperlink should correspond to your predictions dataframe, which you provided the name for or H2O-3 provided a default name for.
  4. Click on the hyperlink in the predictions row or create a new cell, type getFrameSummary "prediction" (without the ` marks, and replace "prediction" with the name of your prediction frame).
  5. Now click on the view data button, and if your binary target is of type enum (i.e. categorical and not numeric) you will see a table with prediction labels and probabilities.