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: Gets the anomaly scores for each sample.
  Each anomaly score is either 0 or 1, where 1 indicates an anomaly.
  
  :return: anomaly score for each sample, in an array format with the same size as input
code: def score(self):
      """
      Gets the anomaly scores for each sample.
      Each anomaly score is either 0 or 1, where 1 indicates an anomaly.
  
      :return: anomaly score for each sample, in an array format with the same size as input
      """
      if self.anomaly_indexes_ is None:
          from bigdl.nano.utils.common import invalidInputError
  
          invalidInputError(False, "Please call fit first")
      return self.anomaly_scores_
  
file_path: BigDL/python/chronos/src/bigdl/chronos/detector/anomaly/dbscan_detector.py
imports: from bigdl.chronos.detector.anomaly.abstract import AnomalyDetector
  from bigdl.chronos.detector.anomaly.util import INTEL_EXT_DBSCAN
  import numpy
label_desc: Use image node_id 4 for calling the DBScanDetector obj's underlying member method code with example usage: obj.score() and returns: self