Affinity Analysis
Affinity analysis falls under the umbrella term of data mining which uncovers meaningful correlations between different entities according to their co-occurrence in a data set. In almost all systems and processes, the application of affinity analysis can extract significant knowledge about the unexpected trends. In fact, affinity analysis takes advantages of studying attributes that go together which helps uncover the hidden pattens in a big data through generating association rules. Association rules mining procedure is two-fold: first, it finds all frequent attributes in a data set and, then generates association rules satisfying some predefined criteria, support and confidence, to identify the most important relationships in the frequent itemset. The first step in the process is to count the co-occurrence of attributes in the data set. Next, a subset is created called the frequent itemset. The association rules mining takes the form of ''if'' a condition or feature (A) is presen ...
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