class_docstr: Example:
      >>> #The dataset to detect is y
      >>> y = numpy.array(...)
      >>> ad = DBScanDetector(eps=0.1, min_samples=6)
      >>> ad.fit(y)
      >>> anomaly_scores = ad.score()
      >>> anomaly_indexes = ad.anomaly_indexes()
docstr: Fit the model
  
  :param y: the input time series. y must be 1-D numpy array.
code: def fit(self, y):
      """
      Fit the model
  
      :param y: the input time series. y must be 1-D numpy array.
      """
      self.check_data(y)
      self.anomaly_scores_ = np.zeros_like(y)
      clusters = DBSCAN(eps=self.eps, min_samples=self.min_samples).fit(
          y.reshape(-1, 1), **self.argv
      )
      labels = clusters.labels_
      outlier_indexes = np.where(labels == -1)[0]
      self.anomaly_indexes_ = outlier_indexes
      self.anomaly_scores_[self.anomaly_indexes_] = 1
  
file_path: analytics-zoo/pyzoo/zoo/chronos/detector/anomaly/dbscan_detector.py
imports: from zoo.chronos.detector.anomaly.abstract import AnomalyDetector
  import numpy
  from sklearn.cluster import DBSCAN
label_desc: Use image node_id 3 for calling the DBScanDetector obj's underlying member method code with example usage: obj.fit(y) without return types