class_docstr: Base Class for AnomalyDetector algorithm.
docstr: Initializer
  :param str class_name: extended class name.
  :param TimeSeries time_series: a TimeSeries object.
  :param TimeSeries baseline_time_series: baseline TimeSeries.
docstr_tok: ["Initializer",":","param","str","class_name",":","extended","class","name",".",":","param","TimeSeries","time_series",":","a","TimeSeries","object",".",":","param","TimeSeries","baseline_time_series",":","baseline","TimeSeries","."]
code: def __init__(
      self, class_name, time_series, baseline_time_series=None
  ):
      """
      Initializer
      :param str class_name: extended class name.
      :param TimeSeries time_series: a TimeSeries object.
      :param TimeSeries baseline_time_series: baseline TimeSeries.
      """
      self.class_name = class_name
      self.time_series = time_series
      self.time_series_length = len(time_series)
      self.baseline_time_series = baseline_time_series
  
file_path: luminol/src/luminol/algorithms/anomaly_detector_algorithms/__init__.py
imports: from luminol.constants import DEFAULT_NOISE_PCT_THRESHOLD
label_desc: Use image node_id 1 to create a new AnomalyDetectorAlgorithm object from inherited base classes: object with example: obj = AnomalyDetectorAlgorithm(class_name, time_series, baseline_time_series)