{'fraction_non_alphanumeric': 0.009977827050997782, 'fraction_numerical': 0.0, 'mean_word_length': 4.940789473684211, '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}}
Association Clustering and Time Series Based Data Mining in Continuous Data for Diabetes Prediction

Large amount of health related data is being produced in various levels of health system. Due to the size of the data it will be difficult to process the data and then extract the analysis. But with the use of different machine learning based approaches data can be processed. Machine learning based approach will provide the efficient data for curing of the patients. Even helps in forecast the future disease. Patients past history for different parameters can contribute to his probability of various health related issues. But using Association clustering and Time Series based data mining in Continuous data early warning system can be developed. This prediction based system can define the disease while analyzing his existing parameters. Some level of care can protect the patient from disease.