class_docstr: Unit test class for correctness of model predictions.
class_docstr_tok: ["Unit","test","class","for","correctness","of","model","predictions","."]
code: def setUpClass(self):
      self.sf = make_classifier_data(n=100, d=2, seed=19)
      self.sf_test = make_classifier_data(n=10, d=2, seed=92)
      self.distance = [
          [
              ["int0", "int1", "float0", "float1", "array0"],
              "euclidean",
              1,
          ],
          [["int0", "int1"], "manhattan", 1.5],
          [["str0"], "levenshtein", 2],
          [["dict0"], "weighted_jaccard", 1.3],
      ]
  
      self.model = tc.nearest_neighbor_classifier.create(
          self.sf, target="class", distance=self.distance, verbose=False
      )
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import copy
  import array
  import numpy
  import turicreate
  from .None import util
  from turicreate.util import _assert_sframe_equal
  from turicreate.toolkits._main import ToolkitError
  import sys
label_desc: Use image node_id 1 for calling the KnnClassifierPredictTest obj's underlying member method code with example usage: obj.setUpClass() without return types