code: def aggregate_proba_ensemble_weighted(ensemble_proba, weights):
      predicted_proba = ensemble_proba * np.expand_dims(weights, axis=2)
      predicted_proba = predicted_proba.mean(axis=1)
  
      return softmax(predicted_proba)
  
imports: import numpy
  from scipy.stats.mstats import mode
  from sklearn.utils.validation import check_array
  from deslib.util.prob_functions import softmax
label_desc: Use image node_id 10 for calling a global function with example usage: aggregate_proba_ensemble_weighted(ensemble_proba, weights) and returns: softmax