class_docstr: Configuration class for an MSES forecasting model adapted for anomaly detection.
class_docstr_tok: ["Configuration","class","for","an","MSES","forecasting","model","adapted","for","anomaly","detection","."]
code: def __init__(
      self,
      max_forecast_steps: int,
      online_updates: bool = True,
      **kwargs,
  ):
      super().__init__(max_forecast_steps=max_forecast_steps, **kwargs)
      self.online_updates = online_updates
  
file_path: merlion/merlion/models/anomaly/forecast_based/mses.py
imports: import pandas
  from merlion.models.anomaly.forecast_based.base import ForecastingDetectorBase
  from merlion.models.anomaly.base import DetectorConfig
  from merlion.models.forecast.smoother import MSESConfig, MSES, MSESTrainConfig
  from merlion.post_process.threshold import AggregateAlarms
  from merlion.utils.time_series import TimeSeries
label_desc: Use image node_id 1 to create a new MSESDetectorConfig object from inherited base classes: MSESConfig, DetectorConfig with example: obj = MSESDetectorConfig(max_forecast_steps, online_updates)