class_docstr: Train/Validation set splitter for sklearn's GridSearchCV etc.
  
  Uses user-specified train/validation set indices to split a dataset
  into train/validation sets using user-defined or random
  indices.
  
  Parameters
  ----------
  valid_indices : array-like, shape (num_examples,)
      Indices of the training examples in the training set
      to be used for validation. All other indices in the
      training set are used to for a training subset
      for model fitting.
  
  Examples
  -----------
  For usage examples, please see
  https://rasbt.github.io/mlxtend/user_guide/evaluate/PredefinedHoldoutSplit/
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code: def __init__(self, valid_indices):
      self.valid_indices = valid_indices
  
file_path: mlxtend/mlxtend/evaluate/holdout.py
imports: import numpy
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 1 to create a new PredefinedHoldoutSplit object from inherited base classes: object with example: obj = PredefinedHoldoutSplit(valid_indices)