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How to let deployed classifier return probabilities?
Description of the problem:
#Let the random-forest model be: rf_model
from kale.common.serveutils import serve kfserver = serve(rf_model) #model is deployed
#prepare data for prediction data = [row.tolist() for _, row in train_df[predictor_var].head(10).iterrows()] data_json = json.dumps({"instances": data})
#prediciton: pred = kfserver.predict(data_json)
Question 1: The returned pred is class labels: 0/1. How to return probabilities?
I tried the following way after studying: kale.common.serveutils.predict #let HOST be the host name of deployed model #let the URL of calling the deployed model be: http://xxx:predict headers = {"content-type": "application/json", "Host": HOST} pred_2 = requests.post(url = URL, data=data_json, headers=headers)
Question 2: But not clear, where to set parameter, so pred_2 will return probabilities?