code: def getPredictionResults(network, clRegionName):
    
    classifierRegion = network.regions[clRegionName]
    actualValues = classifierRegion.getOutputData("actualValues")
    probabilities = classifierRegion.getOutputData("probabilities")
    steps = classifierRegion.getSelf().stepsList
    N = classifierRegion.getSelf().maxCategoryCount
    results = {step: {} for step in steps}
    for i in range(len(steps)):
      # stepProbabilities are probabilities for this prediction step only.
      stepProbabilities = probabilities[i * N:(i + 1) * N - 1]
      mostLikelyCategoryIdx = stepProbabilities.argmax()
      predictedValue = actualValues[mostLikelyCategoryIdx]
      predictionConfidence = stepProbabilities[mostLikelyCategoryIdx]
      results[steps[i]]["predictedValue"] = predictedValue
      results[steps[i]]["predictionConfidence"] = predictionConfidence
    return results
docs: Get prediction results for all prediction steps.