Search Results - (( based classifications rules algorithm ) OR ( using factorization learning algorithm ))

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  1. 1

    On equivalence of FIS and ELM for interpretable rule-based knowledge representation by Wong S.Y., Yap K.S., Yap H.J., Tan S.C., Chang S.W.

    Published 2023
    “…Classification (of information); Computer aided diagnosis; Fault detection; Fuzzy systems; Knowledge acquisition; Knowledge representation; Learning systems; Matrix algebra; Membership functions; Pattern recognition; Extreme learning machine; Fault detection and diagnosis; Fuzzy if-then rules; Fuzzy inference systems; Fuzzy membership function; Initialization technique; Interpretable rules; Rule based; Fuzzy inference; algorithm; artificial intelligence; artificial neural network; benchmarking; classification; electric power plant; factual database; feedback system; fuzzy logic; machine learning; nerve cell; reproducibility; statistical model; Algorithms; Artificial Intelligence; Benchmarking; Classification; Databases, Factual; Feedback; Fuzzy Logic; Machine Learning; Models, Statistical; Neural Networks (Computer); Neurons; Power Plants; Reproducibility of Results…”
    Article
  2. 2

    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 result indicated that the highest accuracy of 89.34% was achieved by the Random Tree algorithm, while the rule-based algorithm PART reached an accuracy of 87.56%. …”
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    Article
  3. 3

    Classification of stock market index based on predictive fuzzy decision tree by Khokhar, Arashid Hafeez

    Published 2005
    “…In particular, predictive FDT algorithm is based on the concept of degree of importance of attribute contributing to the classification. …”
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    Thesis
  4. 4

    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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    Book Section
  5. 5

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

    Published 2018
    “…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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    Thesis
  6. 6

    Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

    Published 2013
    “…Using 10-fold cross validation for each algorithm, it was found that decision tree was the best algorithm with 83.6944% correctness. …”
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    Conference or Workshop Item
  7. 7

    Household overspending model amongst B40, M40 and T20 using classification algorithm by Zulaiha Ali, Othman, Azuraliza, Abu Bakar, Nor Samsiah, Sani, Jamaludin, Sallim

    Published 2020
    “…The model development employs five machine learning algorithms namely decision tree, Naive Bayes, Neural network, Support Vector Machines, Nearest Neighbour. …”
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    Article
  8. 8

    An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

    Published 2018
    “…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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    Thesis
  9. 9

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

    Published 2020
    “…The algorithm’s performance was compared with other variants of Ant-Miner and state-of-the-art rules-based classification algorithms based on classification accuracy and model complexity. …”
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    Thesis
  10. 10

    Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron by Che Haron, Mohammad Bakri

    Published 2013
    “…In this research, Natphoric algorithm is used in order to simulate how the experts find the significant factor of emotions. …”
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    Thesis
  11. 11

    Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2018
    “…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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    Article
  12. 12

    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

    Published 2018
    “…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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    Conference or Workshop Item
  13. 13

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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    Thesis
  14. 14

    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.

    Published 2010
    “…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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    Article
  15. 15

    An application of predicting student performance using kernel k-means and smooth support vector machine by Sajadin, Sembiring

    Published 2012
    “…In this study, psychometric factors used as predictor variables, thereare Interest, Study Behavior, Engaged Time, Believe, and Family Support.The rulemodel developed using Kernel K-means Clustering and Smooth Support Vector MachineClassification.Both of these techniquesbased on kernel methodsand relativelynew algorithms of data mining techniques, recently received increasingly popularity in machine learning community. …”
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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
    “…Henceforth, to achieve the aim, current research work proposed an enhancement of discretization algorithm based on Binning Discretization in RST to improve classification performance and to enhance the strategy of generation rules in RST to improve classification performance. …”
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    Thesis
  17. 17

    A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

    Published 2011
    “…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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    Monograph
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    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Classification rules were generated based on the best reduct. …”
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    Thesis
  20. 20

    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 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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    Article