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  1. 1
    Case Slicing Technique for Feature Selection

    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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  2. 2
    Classification of credit card holder behavior using K Nearest Neighbor algorithm / Ahmad Faris Rahimi

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

    Published 2017
    “…The second one is to develop prototype for classification of credit cardholder behavior based on k Nearest Neighbors Algorithm. …”
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  3. 3
    Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan

    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
    “…The objective was to identify and implement the most accurate algorithm for the KPTM dataset and to come up with a good prediction model using decision tree technique. …”
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  4. 4
    Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment

    Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment by Al-Doski, Jwan M. Mohammed

    Published 2013
    “…In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq. …”
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  5. 5
    BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning

    BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

    Published 2023
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  6. 6
    Fpga-Based Accelerator For The Identification Of Finger Vein Pattern Via K-Nearest Centroid Neighbors

    Fpga-Based Accelerator For The Identification Of Finger Vein Pattern Via K-Nearest Centroid Neighbors by Yew , Tze Ee

    Published 2016
    “…As almost all finger vein recognition algorithms were implemented using software such as MATLAB which is based on general-purpose processor, the processing speed become the bottleneck of the development of finger vein recognition. …”
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  7. 7
    Raspberry Pi-Based Finger Vein Recognition System Using PCANet

    Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

    Published 2018
    “…Factors which impact PCANet are studied to identify the limitations of PCANet. For classification, k-Nearest Neighbours (kNN) with Euclidean distance algorithm is implemented. …”
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  8. 8
    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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  9. 9
    Banana recognition system using convolutional neural network / Mohamad Shafiq Rosli

    Banana recognition system using convolutional neural network / Mohamad Shafiq Rosli by Rosli, Mohamad Shafiq

    Published 2021
    “…The programming is a subject that are used by developer to provide the system. …”
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  10. 10
    Spiking Neural Network For Energy Efficient Learning And Recognition

    Spiking Neural Network For Energy Efficient Learning And Recognition by Wong, Yan Chiew, Wang, Ning Lo

    Published 2020
    “…Common building blocks and techniques used to implement a spiking neural network are investigated to identify design parameters for hardware-based neuron implementations. …”
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  11. 11
    A stylometry approach for blind linguistic steganalysis model against translation-based steganography

    A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

    Published 2023
    “…However, accuracy of blind steganalysis algorithms highly depend on the features selected from the input data especially when attacking embedding techniques in TBS. …”
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  12. 12
    Implementation of Hybrid Indexing, Clustering and Classification Methods to Enhance Rural Development Programme in South Sulawesi

    Implementation of Hybrid Indexing, Clustering and Classification Methods to Enhance Rural Development Programme in South Sulawesi by Muhammad, Faisal

    Published 2024
    “…The classification technique using the CSLI-Cluster, DVI, and HDI criteria showed that as many as 22 villages had the status of Less Development level, and 8 villages were declared Developed. …”
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  13. 13
    Chili crop segregation system design and development strategies

    Chili crop segregation system design and development strategies by Wan Daud, Wan Mohd Bukhari, Abdul Aziz, Mohd Fareezuan, Ahmad Izzuddin, Tarmizi, Norasikin, Mohd Adili, Abdul Rasid, Ahmad Fuad, Wakhi Anuar, Nur Farah Bazilah, M. N. Sukhaimie

    Published 2021
    “…The image data taken from chili samples can be trained by using Learning Algorithm in the MATLAB program. The performance of the trained network then can be evaluated by using the Confusion Matrix technique. …”
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  14. 14
    Feature clustering for pso-based feature construction on high-dimensional data

    Feature clustering for pso-based feature construction on high-dimensional data by Swesi, Idheba Mohamad Ali Omer, Abu Bakar, Azuraliza

    Published 2019
    “…The Redundancy-Based Feature Clustering (RFC) algorithm was applied to choose the most informative features from the original data, while PSO was used to construct new features from those selected by RFC. …”
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  15. 15
    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining

    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

    Published 2025
    “…Furthermore, reliefF-Gradient boosting and random forest algorithms achieved promising overall accuracy of 97.4% and 96.9%, respectively after implementing filtering and feature selection techniques. …”
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  16. 16
    Development of deep learning based user-friendly interface for fruit quality detection

    Development of deep learning based user-friendly interface for fruit quality detection by Mohd Ali, Maimunah, Hashim, Norhashila

    Published 2024
    “…The implementation of deep learning algorithms has contributed to various applications related to the detection of fruit quality. …”
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  17. 17
    An enhancement of classification technique based on rough set theory for intrusion detection system application

    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. …”
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  18. 18
    An adaptive ant colony optimization algorithm for rule-based classification

    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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  19. 19
    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
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  20. 20
    An enhanced feature selection technique for classification of group based holy Quran verses

    An enhanced feature selection technique for classification of group based holy Quran verses by Abdullahi Oyekunle, Adeleke

    Published 2018
    “…Therefore, in this study, a hybrid feature selection technique is proposed. The proposed FS technique is a combination of filter-based information gain (IG) and wrapper-based CFS algorithms. …”
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