This report reviews various class-selective rejection rules for pattern recognition. A rejection rule is called class-selective if it does not reject an ambiguous pattern from all classes but only from those classes that are most unlikely to issue the pattern. Both optimal and suboptimal rules, e.g. top-n ranking, are considered. Experimental comparisons performed on the recognition of isolated...

In this paper, we demonstrate that simple fuzzy rule-based classification systems with high interpretability are obtained through multiobjective genetic rule selection. In our approach, first a prespecified number of candidate fuzzy rules are extracted from numerical data in a heuristic manner using rule evaluation criteria. Then multiobjective genetic rule selection is applied to the extracted...

Feature selection and feature weighting are useful techniques for improving the classification accuracy of K-nearest-neighbor (K-NN) rule. The term feature selection refers to algorithms that select the best subset of the input feature set. In feature weighting, each feature is multiplied by a weight value proportional to the ability of the feature to distinguish pattern classes. In this paper,...

The DPL (Davis-Putnam-Logemann-Loveland) procedure is one of the most effective methods for solving SAT problems. It is well known that its efficiency depends on the choice of the branching rule. One of the main improvements of this decision procedure has been the development of better branching variable selection through the use of unit propagation look-ahead (UPLA) heuristics (e.g., [13]). UP...

This paper describes Rapture | a system for revising probabilistic rule bases that converts symbolic rules into a connectionist network, which is then trained via connectionist techniques. It uses a modi ed version of backpropagation to re ne the certainty factors of the rule base, and uses ID3's information-gain heuristic (Quinlan, 1986) to add new rules. Work is currently under way for nding ...

In this note we present the worst-character rule, an efficient variation of the bad-character heuristic for the exact string matching problem, firstly introduced in the well-known Boyer-Moore algorithm. Our proposed rule selects a position relative to the current shift which yields the largest average advancement, according to the characters distribution in the text. Experimental results show t...

This paper deals with the permutation flow shop scheduling problem. The objective is to minimize the maximum completion time, or makespan. To solve this problem which has been proved to be strongly NP-hard, a combination between an ant colony algorithm, a heuristic algorithm and a local search procedure is proposed and presented. The hybrid approach is to use artificial ants to construct soluti...

During social interactions, groups develop collective competencies that (ideally) should assist groups to outperform average standalone individual members (weak cognitive synergy) or the best performing member in the group (strong cognitive synergy). In two experimental studies we manipulate the type of decision rule used in group decision-making (identify the best vs. collaborative), and the w...

This study focuses on PCB scheduling problem with sequence-dependent setup times on a single machine and feeder capacity constraint. The objective of the scheduling problem is to minimize the total weighted tardiness. The evolutionary algorithms to solve this PCB scheduling problem is an integration of genetic algorithm, local search procedure, heuristic scheduling rule and Keep Tool Needed Soo...

The categorization of inductive reasoning into largely automatic processes (heuristic reasoning) and controlled analytical processes (rule-based reasoning) put forward by dual-process approaches of judgment under uncertainty (e.g., Stanovich & West, 2000) has been primarily a matter of assumption with a scarcity of direct empirical findings supporting it. We used the process dissociation proced...