Search Results - (( java pattern classification algorithm ) OR ( using set selection algorithm ))

Search alternatives:

Refine Results
  1. 1
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  2. 2
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    Optimization of attribute selection model using bio-inspired algorithms

    Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

    Published 2019
    “…The aim of this paper is to investigate the use of bio-inspired search algorithms in producing optimal attribute set. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  4. 4
    An evaluation of feature selection technique for dendrite cell algorithm

    An evaluation of feature selection technique for dendrite cell algorithm by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza

    Published 2014
    “…From the experiment, the Rough Set Genetic Algorithm reduct is found to be the most effect feature selection for dendrite cell algorithm when it generates a consistent result for all evaluation metrics. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  5. 5
    An Alternative Algorithm for Soft Set Parameter Selection using Special Order

    An Alternative Algorithm for Soft Set Parameter Selection using Special Order by Mohammed, Mohammed Adam Taheir, Wan Maseri, Wan Mohd, Ruzaini, Abdullah Arshah, Mungad, M., Sutoyo, Edi, Chiroma, Haruna

    Published 2015
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  6. 6
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  7. 7
    Feature Selection For The Fuzzy Artmap Neural Network Using A Hybrid Genetic Algorithm And Tabu Search [QA76.87. T164 2007 f rb].

    Feature Selection For The Fuzzy Artmap Neural Network Using A Hybrid Genetic Algorithm And Tabu Search [QA76.87. T164 2007 f rb]. by Tang, Weng Chin

    Published 2007
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Feature Selection For The Fuzzy Artmap Neural Network Using A Hybrid Genetic Algorithm And Tabu Search

    Feature Selection For The Fuzzy Artmap Neural Network Using A Hybrid Genetic Algorithm And Tabu Search by Tang, Weng Chin

    Published 2007
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Ant colony optimization for rule induction with simulated annealing for terms selection

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

    Published 2012
    “…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. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  10. 10
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…The rest sets of experiments carried out to evaluate the proposed algorithms. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    A new ant based rule extraction algorithm for web classification

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

    Published 2011
    “…Ant-Miner algorithm is also still lacking in efficiency, accuracy and rule simplicity because of the local minima problem.Therefore, the Ant-Miner algorithm needs to be improved by taking into consideration of the accuracy and rule simplicity criteria so that it could be used to classify Web documents data sets or any large data sets.The best attribute selection method for Web texts categorization is the combination of correlation-based evaluation with random search as the search method.However, this attribute selection method will not give the best performance in attributes reduction. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  12. 12
    SURE-Autometrics algorithm for model selection in multiple equations

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    Swarm negative selection algorithm for electroencephalogram signals classification

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    Academic leadership bio-inspired classification model using negative selection algorithm

    Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

    Published 2015
    “…Several experiments were carried out by using different set of training and testing data-sets to evaluate the accuracy of the proposed model.As a result, the accuracy of the proposed model is considered excellent for academic leadership classification.For future work, in order to enhance the proposed bio-inspired classification model, a comparative study should be conducted using other established artificial immune system classification algorithms i.e. clonal selection and artificial immune network.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  15. 15
    Enhanced feature selections of Adaboost training for face detection using genetic algorithm (GABoost)

    Enhanced feature selections of Adaboost training for face detection using genetic algorithm (GABoost) by Mohd. Zin, Zalhan, Khalid, Marzuki, Yusof, Rubiyah

    Published 2007
    “…With an additional seven new feature types, we show how Genetic Algorithm (GA) can be used, within the Adaboost framework, to find sets of features which can provide better classifiers with a shorter training time. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  16. 16
    Enhanced feature selections of Adaboost training for face detection using genetic algorithm

    Enhanced feature selections of Adaboost training for face detection using genetic algorithm by Mohd. Zin, Zalhan

    Published 2007
    “…The GA carries out an evolutionary search to select features which results in a higher number of feature types and sets selected in less time. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    The new efficient and accurate attribute-oriented clustering algorithms for categorical data

    The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

    Published 2012
    “…Four real-life data sets obtained from University of California Irvine (UCI) machine learning repository and ten synthetically generated data sets are used to evaluate MGR and IG-ANMI algorithms, and other four algorithms are used to compare with these two algorithms. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  18. 18
    Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread

    Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread by Roshahliza, M. Ramli, Noor, Ali O. Abid, Salina, Abdul Samad

    Published 2016
    “…The adaptive selection from a set of multiple adaptive algorithms to operate according to the characteristics of noise signals. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  19. 19
    A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization

    A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization by Jia Hui Ong, Jason Teo

    Published 2018
    “…Hyper-heuristics is an approach that utilizes a set of Low-Level Heuristic (LLH) and a selection mechanism to solve expensive optimization problems. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: