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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…Classification rule induction is one of the problems solved by the Ant-miner algorithm, a variant of ACO, which was initiated by Parpinelli in 2001. …”
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An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…This paper presents a review of related work of ACO rule classification which emphasizes the types of ACO algorithms and issues. …”
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Rule pruning techniques in the ant-miner classification algorithm and its variants: A review by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…Rule-based classification is considered an important task of data classification.The ant-mining rule-based classification algorithm, inspired from the ant colony optimization algorithm, shows a comparable performance and outperforms in some application domains to the existing methods in the literature.One problem that often arises in any rule-based classification is the overfitting problem. …”
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A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

“…In this paper, a two-stage pattern classification and rule extraction system is proposed. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

“…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. The generation of rule is considered a crucial process in data mining and the generated rules are in a huge number. …”
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Experimental study of urban growth pattern classification using moving window algorithm by Ghani N.L.A., Abidin S.Z.Z.

“…Urban growth pattern can be generally categorized as either infill, expansion or outlying growth. Moving window algorithm determines urban growth pattern based on moving window analysis and a set of classification rules. …”

Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

“…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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Hybrid ant colony optimization and genetic algorithm for rule induction by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…In this study, a hybrid rule-based classifier namely, ant colony optimization/genetic algorithm ACO/GA is introduced to improve the classification accuracy of Ant-Miner classifier by using GA. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…It is a useful approach for uncovering classificatory knowledge and building a classification rules. …”
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Rule-based embedded HMMs phoneme classification to improve Qur’anic recitation recognition by Mohammed Ali Alqadasi, Ammar, Sunar, Mohd Shahrizal, Turaev, Sherzod, Abdulghafor, Rawad Abdulkhaleq Abdulmolla, Salam, Md Sah, Alashbi, Abdulaziz Ali Saleh, Ahmed Salem, Ali, Ali, Mohammed A. H.

“…This paper introduces a Rule-Based Phoneme Duration Algorithm to improve phoneme classification in Qur’anic recitation. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…Based on the experiment results, the classification method using the TIP approach has successfully performed rules generation and classification tasks as required during a classification operation. …”
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Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

“…Empirical results show that with a proper combination of data mining and statistical analysis, the framework is capable of eliminating a large number of non-significant, redundant and contradictive rules while preserving relatively valuable high accuracy and coverage rules when used in the classification problem. …”
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A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

“…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…Fuzzy rule is a form of a fuzzy condition and membership function is a generality of indicator function in classical sets. …”
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A genetic algorithm based fuzzy inference system for pattern classification and rule extraction by Wong S.Y., Yap K.S., Li X.

“…However, in the event of having multiple variables coupled with a few features, the classification problem will be getting more sophisticated, as a result human expert may not be able to derive proper rules. …”

Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

“…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

“…The proposed algorithm is a hybrid system which applied fuzzy logic and artificial neural network, which applies fuzzy logic inference to generate a set of fuzzy weighted production rules and applies artificial neural network to train the weights of fuzzy weighted rules for better classification results. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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