title: DBSCAN running out of memory
body: <p>So I have been using DBSCAN for my dataset in order to find and remove outliers, I'm using google COlab which gives me about 25.63 GB of memory. I need to set my eps value over 2.0 but as soon as I go over 2.0 the code uses all memory and it crashes. I really don't know what to do to fix it, I will attatch my code and for toe error messgage, I get none Google COlab just says restarting because it ran out of memory</p>
  
  <p>My code:</p>
  
  <pre><code>import numpy as np
  
  import pandas as pd
  
  import matplotlib.pyplot as plt
  
  %matplotlib inline
  
  from sklearn.cluster import DBSCAN
  
  
  
  df = pd.read_csv('Final After Simple Filtering.csv',index_col=None,low_memory=True)
  
  
  # Dropping columns with low feature importance
  del df['AmbTemp_DegC']
  del df['NacelleOrientation_Deg']
  del df['MeasuredYawError']
  
  
  
  
  
  DBSCAN = DBSCAN(eps = 2.0, min_samples =100).fit_predict(df)
  
  labels = DBSCAN.labels_
  
  
  n_clusters_ = len(set(labels))
  n_noise_ = list(labels).count(-1)
  print('Estimated number of clusters: %d' % n_clusters_)
  print('Estimated number of noise points: %d' % n_noise_)
  
  
  </code></pre>
  
  <p>Thank you.</p>