code: def create_kneighbors_classifier(X, y):
      """Create a sklearn k-neighbors classifier.
  
      param X: The training data.
      type X: numpy.ndarray or pandas.DataFrame
      param y: The training labels.
      type y: numpy.ndarray or pandas.DataFrame
      return: A sklearn k-neighbors classifier.
      rtype: sklearn.neighbors.KNeighborsClassifier
      """
      knn = KNeighborsClassifier()
      model = knn.fit(X, y)
      return model
  
file_path: responsible-ai-toolbox/rai_test_utils/rai_test_utils/models/sklearn/sklearn_model_utils.py
imports: import numpy
  import pandas
  from sklearn import svm
  from sklearn.compose import ColumnTransformer
  from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
  from sklearn.impute import SimpleImputer
  from sklearn.linear_model import LogisticRegression
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import FunctionTransformer, OneHotEncoder, StandardScaler
label_desc: Use image node_id 3 for calling a global function with example usage: create_kneighbors_classifier(X, y) and returns: model