Search Results - (( knowledge feature selection algorithm ) OR ( java application customization algorithm ))

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  1. 1
    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks

    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

    Published 2019
    “…Experiment results on several multimedia applications have shown that the proposed algorithm is competitive compared with the other single-view feature selection algorithms.…”
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  2. 2
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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  3. 3
    Towards a better feature subset selection approach

    Towards a better feature subset selection approach by Shiba, Omar A. A.

    Published 2010
    “…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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  4. 4
    Feature selection algorithms for Malaysian dengue outbreak detection model

    Feature selection algorithms for Malaysian dengue outbreak detection model by Husam I.S. Abuhamad, Azuraliza Abu Bakar, Suhaila Zainudin, Mazura Sahani, Zainudin Mohd Ali

    Published 2017
    “…This research aimed to identify the best features that lead to better predictive accuracy of dengue outbreaks using three different feature selection algorithms; particle swarm optimization (PSO), genetic algorithm (GA) and rank search (RS). …”
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  5. 5
    The significant effect of feature selection methods in spam risk assessment using dendritic cell algorithm

    The significant effect of feature selection methods in spam risk assessment using dendritic cell algorithm by Zainal K., Jali M.Z.

    Published 2024
    conference output::conference proceedings::conference paper
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  6. 6
    The Significant Effect of Feature Selection Methods in Spam Risk Assessment Using Dendritic Cell Algorithm

    The Significant Effect of Feature Selection Methods in Spam Risk Assessment Using Dendritic Cell Algorithm by Zainal, K, Jali, MZ

    Published 2024
    “…This feature selection method then further fed in conjunction with the Dendritic Cell Algorithm (DCA) as the classifier to measure the risk concentration of a spam message. …”
    Proceedings Paper
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  7. 7
    Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification

    Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification by Al-Tashi, Q., Rais, H.M., Abdulkadir, S.J., Mirjalili, S.

    Published 2020
    “…In this paper, a wrapper-based feature selection method is proposed to select the optimal feature subset. …”
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  8. 8
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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  9. 9
    Feature selection for Malaysian medicinal plant leaf shape identification and classification

    Feature selection for Malaysian medicinal plant leaf shape identification and classification by Sainin, Mohd Shamrie, Alfred, Rayner

    Published 2014
    “…Malaysian medicinal plants may be abundant natural resources but there has not been much research done on preserving the knowledge of these medicinal plants which enables general public to know the leaf using computing capability.Therefore, in this preliminary study, a novel framework in order to identify and classify tropical medicinal plants in Malaysia based on the extracted patterns from the leaf is presented.The extracted patterns from medicinal plant leaf are obtained based on several angle features.However, the extracted features create quite large number of attributes (features), thus degrade the performance most of the classifiers.Thus, a feature selection is applied to leaf data and to investigate whether the performance of a classifier can be improved.Wrapper based genetic algorithm (GA) feature selection is used to select the features and the ensemble classifier called Direct Ensemble Classifier for Imbalanced Multiclass Learning (DECIML) is used as a classifier.The performance of the feature selection is compared with two feature selections from Weka.In the experiment, five species of Malaysian medicinal plants are identified and classified in which will be represented by using 65 images.This study is important in order to assist local community to utilize the knowledge and application of Malaysian medicinal plants for future generation.…”
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  10. 10
    Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim

    Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim by Halim, Zulkifli

    Published 2023
    “…The features are selected based on the extensive literature on CCRA studies worldwide. …”
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  11. 11
    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images

    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

    Published 2014
    “…The high accuracy of object-based classification can be linked to the knowledge discovery produced by the DM algorithm. This algorithm increased the productivity of OBIA, expedited the process of attribute selection, and resulted in an easy-to-use representation of a knowledge model from a decision tree structure.…”
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  12. 12
    Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction

    Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction by Nasser, Abdullah, H.M. Ghanem, Waheed Ali, H.Y. Saad, Abdul-Malik, Hamed Abdul-Qawy, Antar Shaddad, A. Ghaleb, Sanaa A, Mohammed Alduais, Nayef Abdulwahab, Din, Fakhrud, Ghetas, Mohamed

    Published 2024
    “…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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  13. 13
    Bayesian Network Classifiers for Damage Detection in Engineering Material

    Bayesian Network Classifiers for Damage Detection in Engineering Material by Mohamed Addin, Addin Osman

    Published 2007
    “…Feature selection is less °exible than feature extrac- tion in that feature selection is, in fact, a special case of feature extraction (with a coe±cient of one for each selected feature and a coe±cient of zero for any of the other features). …”
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  14. 14
    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO

    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

    Published 2014
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  15. 15
    An extended ID3 decision tree algorithm for spatial data

    An extended ID3 decision tree algorithm for spatial data by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2011
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  16. 16
    Feature Selection and Ensemble Meta Classifier for Multiclass Imbalance Data Learning

    Feature Selection and Ensemble Meta Classifier for Multiclass Imbalance Data Learning by Sainin, Mohd Shamrie, Alfred, Rayner, Alias, Suraya, Lammasha, Mohamed A.M.

    Published 2018
    “…There are two feature selection approaches implemented which are filter-based (CfsSubsetEval, ConsistencySubsetEval and FilteredSubsetEval) and wrapper-based (WrapperSubsetEval). …”
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  17. 17
    Identifying significant features and data mining techniques in predicting cardiovascular disease / Mohammad Shafenoor Amin

    Identifying significant features and data mining techniques in predicting cardiovascular disease / Mohammad Shafenoor Amin by Mohammad Shafenoor , Amin

    Published 2018
    “…A thorough analysis of the features needs to be conducted to select a combination of significant features that can increase the accuracy of the prediction. …”
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  18. 18
    A knowledge based system for automatic classification of web pages

    A knowledge based system for automatic classification of web pages by Fathy, Sherif Kassem

    Published 2006
    “…The paper describes design and implementation of a new knowledge based system for Automatic Information Retrieval DataBase (AIRDB).AIRDB helps the end-user to cluster and classify web pages on the basis of information filtering combined with an Artificial Neural Network (ANN).The classification depends mainly on keyword indexes.A large sample set consists of 11043 web pages of several formats are collected automatically and randomly from various resources.The AIRDB feature selection algorithm is summarized.The feature selection depends upon stemming words of web page. …”
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  19. 19
    Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques

    Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by AHMAD, IFTIKHAR

    Published 2011
    “…Based on the selected features, the classification is performed. …”
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  20. 20
    Feature selection for financial data classification: Islamic finance application

    Feature selection for financial data classification: Islamic finance application by Kartiwi, Mira, Gunawan, Teddy Surya, Arundina, Tika, Omar, Mohd. Azmi

    Published 2019
    “…One of the most critical steps in data mining is data preprocessing, as it would directly affect the quality of insights obtained at the later stage. Feature selection has been widely used in data preprocessing phase to improve the machine learning algorithm and model interpretability. …”
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