{'fraction_non_alphanumeric': 0.00850546780072904, 'fraction_numerical': 0.0, 'mean_word_length': 4.885714285714286, '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}}
DESIGN AND IMPLEMENTATION OF AN ALGORITHM FOR PCA BASED FACTOR ANALYSIS AND CLUSTERING APPLIED TO DERMATOLOGY DATA SET

Medical data mining has immense potential for exploring the hidden patterns in the medical data and the patterns could be utilized for clinical diagnosis. Medical databases are of high dimension and the increase in the dimensionality of data gives rise to a number of new computational challenges not only due to the record size but also due to the increase in the number of attributes. This paper makes an attempt to analyze the dermatology data set by using PCA-based factor analysis (PBF) and clustering analysis. An algorithm for the PBF is proposed and implemented and the predicted results would help the physician to make right predictions at right time so that the patients could be comfortable.