예제 #1
0
def main(inputPath):
    inputFileName = ntpath.basename(inputPath)
    dataFrame = getDataFrame(inputPath)
    model = createPredictionModel(dataFrame)
    outputFrame = runDataThroughModel(model, dataFrame)
    if not os.path.exists(OUTPUT_DIR):
        os.makedirs(OUTPUT_DIR)
    outputFrame.to_csv(os.path.join(OUTPUT_DIR, "prediction_" + inputFileName),
                       index=False)
예제 #2
0
def main(inputPath):
  inputFileName = ntpath.basename(inputPath)
  dataFrame = getDataFrame(inputPath)
  model = createAnomalyDetectionModel(dataFrame)
  outputFrame = runDataThroughModel(model, dataFrame)
  if not os.path.exists(OUTPUT_DIR):
    os.makedirs(OUTPUT_DIR)
  outputFrame.to_csv(
    os.path.join(OUTPUT_DIR, "anomaly_" + inputFileName),
    index=False
  )
예제 #3
0
def main(inputPath): # data/nyc_taxi.csv 
  inputFileName = ntpath.basename(inputPath) # nyc_taxi.csv
  dataFrame = getDataFrame(inputPath)
  #                  timestamp  value
  # 0      2014-07-01 00:00:00  10844
  # 1      2014-07-01 00:30:00   8127
  # 2      2014-07-01 01:00:00   6210 
  model = createPredictionModel(dataFrame)
  outputFrame = runDataThroughModel(model, dataFrame)
  if not os.path.exists(OUTPUT_DIR):
    os.makedirs(OUTPUT_DIR)
  outputFrame.to_csv(
    os.path.join(OUTPUT_DIR, "prediction2_" + inputFileName),
    index=False
  )