{'fraction_non_alphanumeric': 0.012552301255230125, 'fraction_numerical': 0.0, 'mean_word_length': 5.141025641025641, '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}}
Comparison of classical and Bayesian models using BLR

The modeling of storage reliability using binary logistic regression allows for one to explore the causal or correlative variable relationships that affect the outcome of binary (pass/fail) tests. Both classical and Bayesian models show good agreement when the amount of data available is large as it should. Bayesian models should add some value for situations in which there are only small amounts of testing information.