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Warn if eps is not specificed for DBSCAN #13541

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Warn if eps is not specificed for DBSCAN #13541

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15 changes: 11 additions & 4 deletions sklearn/cluster/dbscan_.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,8 @@
#
# License: BSD 3 clause

import warnings

import numpy as np
import warnings
from scipy import sparse
Expand All @@ -20,9 +22,9 @@
from ._dbscan_inner import dbscan_inner


def dbscan(X, eps=0.5, min_samples=5, metric='minkowski', metric_params=None,
algorithm='auto', leaf_size=30, p=2, sample_weight=None,
n_jobs=None):
def dbscan(X, eps='warn', min_samples=5, metric='minkowski',
metric_params=None, algorithm='auto', leaf_size=30, p=2,
sample_weight=None, n_jobs=None):
"""Perform DBSCAN clustering from vector array or distance matrix.

Read more in the :ref:`User Guide <dbscan>`.
Expand Down Expand Up @@ -136,6 +138,11 @@ def dbscan(X, eps=0.5, min_samples=5, metric='minkowski', metric_params=None,
DBSCAN revisited, revisited: why and how you should (still) use DBSCAN.
ACM Transactions on Database Systems (TODS), 42(3), 19.
"""
if eps == 'warn':
warnings.warn("There is no good default value for the 'eps' "
"parameter of DBSCAN. Because of legacy reasons, "
"sklearn uses eps=0.5 as default.")
eps = 0.5 # use old default value
if not eps > 0.0:
raise ValueError("eps must be positive.")

Expand Down Expand Up @@ -316,7 +323,7 @@ class DBSCAN(BaseEstimator, ClusterMixin):
ACM Transactions on Database Systems (TODS), 42(3), 19.
"""

def __init__(self, eps=0.5, min_samples=5, metric='euclidean',
def __init__(self, eps='warn', min_samples=5, metric='euclidean',
metric_params=None, algorithm='auto', leaf_size=30, p=None,
n_jobs=None):
self.eps = eps
Expand Down