Mining of Frequent Patterns is the process of mining patterns that frequently occurs in data. Data can be described with classes or concepts. These descriptions are inferred with data characterization and data discrimination. Data characterization is the process of summarizing the general properties of a class whereas data discrimination is the process of comparing class properties with features of other one or more classes. Association is referred as patterns frequently purchased together. Mining association is the process of discovering relations among data. Correlations represent relations between items or their attributes. Two items can be positively or negatively correlated. Moreover, there may be no correlation between two items as a result of mining correlation. Clustering brings together similar objects which do not have a class label. Therefore, the correct option is E.