docs/examples/network/complete-network-example.py
def getPredictionResults(network, clRegionName):
  """Get prediction results for all prediction steps."""
  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
def getPredictionResults(network, clRegionName):
  """Get prediction results for all prediction steps."""
  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
Get prediction results for all prediction steps.