docstr: Predict class for a single sample.
docstr_tok: ["Predict","class","for","a","single","sample","."]
code: def _predict(self, inputs):
      """Predict class for a single sample."""
      node = self.tree_
      while node.left:
          if inputs[node.feature_index] < node.threshold:
              node = node.left
          else:
              node = node.right
      return node.predicted_class
  
imports: import numpy
  import ray
  from sklearn import datasets, metrics
  import time
  import tempfile
  import os
  import json
label_desc: Use image node_id 8 for calling the DecisionTreeClassifier obj's underlying member method code with example usage: obj._predict(inputs) and returns: node