How to group every data point with HDBSCAN to some group to have no noise?
DBSCAN will always mark noisy points according to epsilon and min_samples parameters, so there is no way to avoid that unless you have very compact and &quot;well defined&quot; clusters, what seems unlikely.The short answers will be to use another clustering algorithm such as gaussian mixture, k-means, or Birch
If your problem really needs you to use DBSCAN, you can try performing a quantile tranformation (uniform) prior clustering
Example:
scaler = Pipeline([(&quot;imputer&quot;, SimpleImputer(strategy= &quot;constant&quot;, fill_value= 0)),(&quot;transformer&quot;, QuantileTransformer(output_distribution = &quot;uniform&quot;))])

model = Pipeline([(&quot;scaler&quot;, scaler), (&quot;cluster&quot;,HDBSCAN(min_cluster_size=10, min_samples=1))]).fit(data)