… 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 …

… 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 …

… 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 …

… 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 …

… , a novel and efficient detector named YOLO-ACN is presented. The detector model is … -ACN
has high accuracy and speed in detecting small targets and occluded objects. YOLO-ACN …

… ACN-activated Sep-Pak® columns, washed with 12 mL of 0.1% TFA, and eluted with 50%
ACN … associated with WP cluster 2, while negative regulation of response to DNA damage was …

… basis of flowering time regulation is expected to lead to the … Another negative effect of
climate change is the alteration of … expression and the regulation of PA/ACN biosynthesis in ET-…

… composed of an associative search network (ASN) and an adaptive critic network (ACN).
The … This section is aimed to propose an intelligent ORFBLS-ARLFC law using ITSMC for the …