def __init__(self, time_series, baseline_time_series=None, smoothing_factor=<NUM_LIT:0>, use_lag_window=False, lag_window_size=None):
super(ExpAvgDetector, self).__init__(self.__class__.__name__, time_series, baseline_time_series)<EOL>self.use_lag_window = use_lag_window<EOL>self.smoothing_factor = smoothing_factor if smoothing_factor > <NUM_LIT:0> else DEFAULT_EMA_SMOOTHING_FACTOR<EOL>self.lag_window_size = lag_window_size if lag_window_size else int(self.time_series_length * DEFAULT_EMA_WINDOW_SIZE_PCT)<EOL>self.time_series_items = self.time_series.items()<EOL>
Initializer
:param TimeSeries time_series: a TimeSeries object.
:param TimeSeries baseline_time_series: baseline TimeSeries.
:param float smoothing_factor: smoothing factor for computing exponential moving average.
:param int lag_window_size: lagging window size.