… based on closed frequent itemsets [16], L3: Live and Let Live Lazy Associative Classifier [17],
ACN: An associative classifier with negative rules [18], ACCR: Association classification …

… In addition, existing associative classification (AC) methods pay little attention to the rule …
confidence and breaking ties with support has a negative impact on the result. One could assert …

… technique based on class discriminative association rules (… any false positive or false
negative. DISSparse is a heuristic-… We compare the DAC with ACN as in Table 4. Here, we used …

… A new method-ACN was proposed in [6] for classification which extracts positive, negative
association rules and uses these rules in support of classification. The accuracy of the …

… P is the number of negative instances and positive instances respectively; N∗ and P∗ are
the number of both the number negative and positive instances satisfying the rule body. When …

… In the classification stage primarily, this study proposed to integrating principles of fuzzy soft
set theory into associative rules, therefore referred to as Class-Based Fuzzy Soft Associative …

… They are also very useful for constructing associative classifiers. In this paper, we propose
an algorithm that mines positive and negative association rules without adding any additional …

… ' rules and in associative classification we perform classification using association rules only…
include ARC-BC [8], Negative Rules [9], CAAR [41], and ACN [24]. To further improve upon …

… Many factors, such as long-term exposure to negative feelings … In fact, Associative classifiers
extract first association rules [5] … other associative classifiers, such as ARC-BC [4], ACN [20]. …

… negative but strong rules, we generated a set of negative features by reversing the positive
and negative … has 43,668 positive cases and 482,455 negative cases. The dataset is very …