{'fraction_non_alphanumeric': 0.012755102040816327, 'fraction_numerical': 0.002551020408163265, 'mean_word_length': 5.487603305785124, '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}}
Predicting Diabetes Implementing Hybrid Approach

Medically stated diabetes is the outcome when glucose/sugar level is high. Blood glucose is the key category of sugar and major foundation of energy. Hybrid approach is used to extract knowledge related diabetes from medical information source as database and helps to generate clear and understandable diagnosis of the problem as well as implementing medical diagnosis. This work orients towards the progress of a hybrid form based on Pima Indian diabetic database (PIDD).Experimental results indicate that the proposed method along with preprocessing produces better result with classification accuracy of 86%. In this study different algorithms are implemented to predict whether a patient having diabetes along its severity level.