ref: SVR has no random_state

AFM-analysis · Nov 5, 2018 · c623c88 · c623c88
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diff --git a/docs/sec_rating_workflow.rst b/docs/sec_rating_workflow.rst
@@ -16,10 +16,12 @@ Nanite already comes with a default training set that is based on AFM
 data recorded for zebrafish spinal cord sections, called `zef18`.
 The original dataset is available on figshare :cite:`zef18`.
 Download links:
-(SHA256 sum: 63d89a8aa911a255fb4597b2c1801e30ea14810feef1bb42c11ef10f02a1d055).
 
 - https://ndownloader.figshare.com/files/13481393
 
+(SHA256: 63d89a8aa911a255fb4597b2c1801e30ea14810feef1bb42c11ef10f02a1d055)
+
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 With nanite, you can also create your own training set. The required steps
 to do so are described in the following.
 

diff --git a/nanite/rate/regressors.py b/nanite/rate/regressors.py
@@ -57,7 +57,6 @@
         {"kernel": "rbf",
          "C": 25,
          "epsilon": 0.7,
-         "random_state": 42,
          },
     ],
 }