Search Results - (( generation classification rules algorithm ) OR ( using function method algorithm ))

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  1. 1

    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. …”
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    Undergraduates Project Papers
  2. 2

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

    Published 2000
    “…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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    Thesis
  3. 3

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

    Published 2005
    “…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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    Thesis
  4. 4

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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    Thesis
  5. 5

    Discovering decision algorithm from a distance relay event report by Othman, Mohammad Lutfi, Aris, Ishak, Abdullah, Senan Mahmood, Ali, Md. Liakot, Othman, Mohammad Ridzal

    Published 2009
    “…In helping the protection engineers deal with this overwhelming data, this study relied merely on digital protective relay’s recorded event report because, among other intelligent electronic devices, digital protective relay sufficiently provided virtually most attributes needed for data mining process in knowledge discovery in database. The method of discovering the distance relay decision algorithm essentially involved formulating rough set discernibility matrix and function from relay event report, finding reducts of pertinent attributes using genetic algorithm and finally generating relay prediction rules. …”
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    Article
  6. 6

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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    Thesis
  7. 7

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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    Thesis
  8. 8

    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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    Thesis
  9. 9

    An interpretable fuzzy-ensemble method for classification and data analysis / Adel Lahsasna by Adel, Lahsasna

    Published 2016
    “…In addition, we propose a combination method that aims to improve the accuracy of the fuzzy rule-based system by using the accurate ensemble method to classify the patterns that have low certainty degree or in cases of rejected and uncovered classifications. …”
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    Thesis
  10. 10

    Informative top-k class associative rule for cancer biomarker discovery on microarray data by Ong, Huey Fang, Mustapha, Norwati, Hamdan, Hazlina, Rosli, Rozita, Mustapha, Aida

    Published 2020
    “…Nevertheless, more studies are needed on improving the predictability of the discovered gene biomarkers, as well as their reproducibility and interpretability, to qualify them for clinical use. This paper proposes an informative top-k class associative rule (iTCAR) method in an integrative framework for identifying candidate genes of specific cancers. iTCAR introduces an enhanced associative classification algorithm that integrates microarray data with biological information from gene ontology, KEGG pathways, and protein-protein interactions to generate informative class associative rules. …”
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    Article
  11. 11

    Informative top-k class associative rule for cancer biomarker discovery on microarray data by Ong, Huey Fang, Mustapha, Norwati, Hamdan, Hazlina, Rosli, Rozita, Mustapha, Aida

    Published 2020
    “…Nevertheless, more studies are needed on improving the predictability of the discovered gene biomarkers, as well as their reproducibility and interpretability, to qualify them for clinical use. This paper proposes an informative top-k class associative rule ( i TCAR) method in an integrative framework for identifying candidate genes of specific cancers. i TCAR introduces an enhanced associative classification algorithm that integrates microarray data with biological informa- tion from gene ontology, KEGG pathways, and protein-protein interactions to generate informative class associative rules. …”
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    Article
  12. 12

    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

    Published 2021
    “…The LP’s application is need to be further computed with a technique and Simplex algorithm is the one that commonly used. The Simplex algorithm has three stages of computation namely initialization, iterative calculation and termination. …”
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    Thesis
  13. 13

    Generating type 2 trapezoidal fuzzy membership function using genetic tuning by Khairuddin, S.H., Hasan, M.H., Akhir, E.A.P., Hashmani, M.A.

    Published 2022
    “…The system starts with identifying input from data, applying the fuzziness to input using membership functions (MF), generating fuzzy rules for the fuzzy sets and obtaining the output. …”
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    Article
  14. 14

    Generating type 2 trapezoidal fuzzy membership function using genetic tuning by Khairuddin, S.H., Hasan, M.H., Akhir, E.A.P., Hashmani, M.A.

    Published 2022
    “…The system starts with identifying input from data, applying the fuzziness to input using membership functions (MF), generating fuzzy rules for the fuzzy sets and obtaining the output. …”
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    Article
  15. 15

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

    Published 2013
    “…Previous studies have shown that ACO is a promising machine learning technique to generate classification rules. However, the Ant-miner is less class focused since the rule’s class is assigned after the rule was constructed. …”
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    Thesis
  16. 16

    An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

    Published 2019
    “…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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    Thesis
  17. 17

    Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

    Published 2014
    “…Works on sustaining the interestingness of rules generated by data mining algorithms are actively and constantly being examined and developed. …”
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    Article
  18. 18

    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

    Published 2011
    “…The generated adaptive fuzzy inference engine is adjusted by the least-squares fit and a conjugate gradient descent algorithm towards better performance with a minimal set of rules. …”
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    Conference or Workshop Item
  19. 19

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

    Published 2020
    “…In our proposed hybrid ACO/GA algorithm, the ACO is responsible for generating classification rules and the GA improves the classification rules iteratively using the principles of multi-neighborhood structure (i.e., mutation and crossover) procedures to overcome the local optima problem. …”
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    Article
  20. 20

    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. …”
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    Article