{'fraction_non_alphanumeric': 0.010810810810810811, 'fraction_numerical': 0.0, 'mean_word_length': 4.888888888888889, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Learning bagged models of dynamic systems

In this paper, we present an ensemble learning method for modeling dynamic systems. The method is a combination of the bagging approach to ensemble learning and the approach of inductive process modeling of dynamic systems. We illustrate the use of the proposed method on the task of modeling phytoplankton growth in Lake Bled.