class_docstr: In-memory results.
docstr: Load predictions for all datasets and strategies iteratively.
docstr_tok: ["Load","predictions","for","all","datasets","and","strategies","iteratively","."]
code: def load_predictions(self, cv_fold, train_or_test):
      """Load predictions for all datasets and strategies iteratively."""
      for strategy_name, dataset_name in self._iter():
          key = self._generate_key(
              strategy_name, dataset_name, cv_fold, train_or_test
          )
          yield self.results[key]
  
imports: import os
  import numpy
  import pandas
  from joblib import load
  from sktime.benchmarking.base import BaseResults, HDDBaseResults, _PredictionsWrapper
label_desc: Use image node_id 3 for calling the RAMResults obj's underlying member method code with example usage: obj.load_predictions(cv_fold, train_or_test) without return types