code: def __init__(
      self,
      eps=0.5,
      *,
      min_samples=5,
      metric="euclidean",
      metric_params=None,
      algorithm="auto",
      leaf_size=30,
      p=None,
      n_jobs=None,
  ):
      self.eps = eps
      self.min_samples = min_samples
      self.metric = metric
      self.metric_params = metric_params
      self.algorithm = algorithm
      self.leaf_size = leaf_size
      self.p = p
      self.n_jobs = n_jobs
  
file_path: scikit-learn-intelex/onedal/cluster/dbscan.py
imports: import numpy
  from sklearn.base import ClusterMixin
  from sklearn.utils import check_array
  from daal4py.sklearn._utils import get_dtype, make2d
  from onedal import _backend
  from ..common._policy import _get_policy
  from ..datatypes import _convert_to_supported, from_table, to_table
label_desc: Use image node_id 1 to create a new BaseDBSCAN object from inherited base classes: ClusterMixin with example: obj = BaseDBSCAN(eps)