Search Results - (( problem using cross algorithm ) OR ( java implication based algorithm ))

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    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi by Rahimi, Ahmad Faris

    Published 2017
    “…Testing of the application are using 10-Fold Cross Validation technique. 90% of the data be used as a training and another 10% be used for the testing part. …”
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    Thesis
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    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…The experiment was executed by using k-fold cross validation techniques for predicting the classification algorithm performance. …”
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  4. 4

    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 AntMiner classifier is efficient, useful and commonly used for solving rulebased classification problems in data mining. …”
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    Optimization of job scheduling in a machine shop using genetic algorithm by Adhikari, A., Biswas, C.K., Adhikari, N.

    Published 2002
    “…Computer runs were carried out with these parameters at various levels and the results indicated that, only probability of mutation, the combined effect of maximum generation and probability of crossing are significant at 10. It is suggested that the minimum values of these parameters be used for scheduling problems.…”
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  7. 7

    Optimization of job scheduling in a machine shop using genetic algorithm by Adhikari, A., Biswas, C.K., Adhikari, N.

    Published 2002
    “…Computer runs were carried out with these parameters at various levels and the results indicated that, only probability of mutation, the combined effect of maximum generation and probability of crossing are significant at 10. It is suggested that the minimum values of these parameters be used for scheduling problems.…”
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    Article
  8. 8

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Case Slicing Technique (CST) helps in identifying the subset of features used in computing the similarity measures needed by classification algorithms. …”
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    3D face registration across pose variation and facial expression using cross profile alignment by Anuar, Laili Hayati

    Published 2011
    “…The proposed thesis uses a local-based approach known as Cross Profile Alignment (CPA) as an alternative to the global-based approach, utilizing the facial feature of a face surface as an attempt to cater all the above problems. …”
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    Flexible job shop scheduling using priority heuristics and genetic algorithm by Farashahi, Hamid Ghaani

    Published 2010
    “…Then, the validation of proposed genetic algorithm with reinforced initial population (GA2) has been checked with random keys genetic algorithm (RKGA). …”
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    Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation by Din, Abdul Sattar

    Published 2013
    “…The performance of the algorithm was validated and compared against that of the EKF through series of simulations using Stage multi-agent simulator. …”
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    HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION by GHADA HAMMAD AL-RAWASHDEH

    Published 2022
    “…For the training and validation datasets, cross-validation was performed, and seven datasets were used to evaluate the suggested spam classification…”
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    Towards cross-site scripting vulnerability detection in mobile web applications by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia Indriaty

    Published 2018
    “…It proposes an enhanced genetic algorithm-based approach that detects cross-site scripting vulnerabilities in mobile versions of web applications. …”
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    Mitigating imbalanced classification problems in academic performance with resampling methods / A’zraa Afhzan Ab Rahim and Norlida Buniyamin by Ab Rahim, A’zraa Afhzan, Buniyamin, Norlida

    Published 2023
    “…This can create problems when predicting academic performance using machine learning algorithms, which assume that the datasets have a balanced distribution across all classes. …”
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