Search Results - (( model classification rules algorithm ) OR ( java simulation optimization algorithm ))

Refine Results
  1. 1

    An adaptive ant colony optimization algorithm for rule-based classification by Al-Behadili, Hayder Naser Khraibet

    Published 2020
    “…Differing from other complex and difficult classification models, rules-based classification algorithms produce models which are understandable for users. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

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

    Published 2013
    “…Thus, this thesis proposed two variants of hybrid ACO with simulated annealing (SA) algorithm for solving problem of classification rule induction. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…The accuracy of the classification rules by the proposed models was high compared to other models.…”
    Get full text
    Get full text
    Thesis
  4. 4

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…Therefore generating a good decision model or classification model is a major component in many data mining researches. …”
    Get full text
    Get full text
    Thesis
  5. 5
  6. 6

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
    Get full text
    Get full text
    Get full text
    Undergraduates Project Papers
  7. 7

    Hybrid ant colony optimization and genetic algorithm for rule induction by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…The performance of the proposed classifier was tested against other existing hybrid ant-mining classification algorithms namely, ACO/SA and ACO/PSO2 using classification accuracy, the number of discovered rules and model complexity. …”
    Get full text
    Get full text
    Get full text
    Article
  8. 8
  9. 9

    Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength by Hussain Talpur, Kashif

    Published 2015
    “…The AMBA is then employed in proposed effective technique for optimizing ANFIS rule-base. The ANFIS optimized by AMBA is used employed to model classification of Malaysian small medium enterprises (SMEs) based on strength using non-financial factors. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11

    Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

    Published 2002
    “…The experimental results showed that the proposed SIPIDRIP method is a successful method in rough classification modeling. The outstanding feature of this method is the reduced number of rules in all classification models. …”
    Get full text
    Get full text
    Thesis
  12. 12

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

    Published 2018
    “…GAFL possessed the advantage of fuzzy rules extraction feature apart from conventional classification technique compared to other models which are lack of fuzzy interpretation. …”
    Get full text
    Get full text
    Article
  13. 13

    Compressing and improving fuzzy rules using genetic algorithm and its application to fault detection by Yap K.S., Wong S.Y., Tiong S.K.

    Published 2023
    “…The improved model is applied to two benchmark problems, and the rules extracted are analyzed, discussed and compared with other published methods. …”
    Conference Paper
  14. 14

    Dingle's Model-based EEG Peak Detection using a Rule-based Classifier by Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai

    Published 2015
    “…The algorithm is developed into three stages: peak candidate detection, feature extraction, and classification. …”
    Get full text
    Get full text
    Conference or Workshop Item
  15. 15

    Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman by Abdul Aziz, Maslina, Mustakim, Nurul Ain, Abdul Rahman, Shuzlina

    Published 2024
    “…The current study contributes to the literature by highlighting decision tree and rule-based classification models as very useful in the Malaysian e-commerce context. …”
    Get full text
    Get full text
    Article
  16. 16

    A genetic algorithm based fuzzy inference system for pattern classification and rule extraction by Wong S.Y., Yap K.S., Li X.

    Published 2023
    “…The impetus for developing a new and efficient GA-FIS model arises from the need of constructing fuzzy rules directly from raw data sets that combines good approximation and classification properties with compactness and transparency. …”
    Article
  17. 17

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

    Published 2011
    “…A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. …”
    Get full text
    Get full text
    Article
  18. 18

    Irrelevant feature and rule removal for structural associative classification by Mohd Shaharanee, Izwan Nizal, Jamil, Jastini

    Published 2015
    “…In the classification task, the presence of irrelevant features can significantly degrade the performance of classification algorithms,in terms of additional processing time, more complex models and the likelihood that the models have poor generalization power due to the over fitting problem.Practical applications of association rule mining often suffer from overwhelming number of rules that are generated, many of which are not interesting or not useful for the application in question.Removing rules comprised of irrelevant features can significantly improve the overall performance.In this paper, we explore and compare the use of a feature selection measure to filter out unnecessary and irrelevant features/attributes prior to association rules generation.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data items.Empirical results confirm that by utilizing feature subset selection prior to association rule generation, a large number of rules with irrelevant features can be eliminated.More importantly, the results reveal that removing rules that hold irrelevant features improve the accuracy rate and capability to retain the rule coverage rate of structural associative association.…”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    IP algorithms in compact rough classification modeling by Bakar, Azuraliza Abu, Sulaiman, Md Nasir, Othman, Mohamed, Selamat, Mohd Hasan

    Published 2001
    “…The paper presents the Integer Programming (IP) algorithms in mining a compact rough classification model. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

    Published 2021
    “…This study implements a machine learning algorithm called Ant Colony Optimization (ACO) algorithm to develop an accurate classification model for predicting breast cancer cells. …”
    Get full text
    Get full text
    Student Project