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  1. 1
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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  2. 2
    Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation

    Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Mohamed, Shakir, Qidwai, Uvais, Malik, Aamir Saeed, Kamel , Nidal

    Published 2015
    “…A novel work has been done in producing simulated data based on empirical models of the real waveforms. …”
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  3. 3
    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)

    Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224) by Mahat, Nor Idayu, Engku Abu Bakar, Engku Muhammad Nazri, Zakaria, Ammar, Mohd Nazir, Mohd Amril Nurman, Misiran, Masnita

    “…This study developed an algorithm for statistical classification that enable ones to classify a future data to one of predetermined groups based on the measured data which facing two major threats; (i) multicollinearity among the measured variables and (ii) imbalanced groups. …”
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    Monograph
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  4. 4
    EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation

    EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Shakir, Mohamed, Qidwai, Uvais, Malik, Aamir Saeed, Kamel, Nidal

    Published 2015
    “…A novel work has been done in producing simulated data based on empirical models of the real waveforms. …”
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    Citation Index Journal
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  5. 5
    Cyberbullying detection: a machine learning approach

    Cyberbullying detection: a machine learning approach by Yeong, Su Yen

    Published 2022
    “…Machine learning is a hot topic and it is widely implemented in software, web application and more. Those algorithms are used in the classification or regression model to predict an input. …”
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  6. 6
    A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh

    A voting-based hybrid machine learning approach for fraudulent financial data classification / Kuldeep Kaur Ragbir Singh by Kuldeep Kaur , Ragbir Singh

    Published 2019
    “…In addition to the standard hybrid approach, a sliding window method is further evaluated using the real-world credit card data, with the aim to simulate and assess the capability of real-time identification of fraud cases at the financial institution. …”
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  7. 7
    Embedded wearable EEG seizure detection in ambulatory state

    Embedded wearable EEG seizure detection in ambulatory state by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…This paper describes a classification method is presented using a Fuzzy System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. …”
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  8. 8
    Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine

    Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine by Raad Ali, Rabei

    Published 2019
    “…These datasets have complex challenges that simulate particular fragmentation cases addressed in this research. …”
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  9. 9
    Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State

    Fuzzy Platform for Embedded Wearable EEG Seizure Detection in Ambulatory State by Shakir, Mohamed, Malik, Aamir Saeed, Kamel , Nidal, Qidwai, Uvais

    Published 2014
    “…This gives an enhanced advantage over the existing EEG based seizure detection systems due to their complex pattern classification methodologies. …”
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  10. 10
    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques

    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…To validate the research, the researcher presents case study using GLOMOSIM simulation platform with AODV ad hoc routing protocols. …”
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  11. 11
    Case Slicing Technique for Feature Selection

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

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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  12. 12
    Forward scattering radar for real-time detection of human activities and fall classification

    Forward scattering radar for real-time detection of human activities and fall classification by Abdulhameed, Ali Ahmed

    Published 2019
    “…The frequency spectrum signatures extracted from the experimentally collected data were used as input features to the classification unit. …”
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  13. 13
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Classification is a process of grouping or placing data into appropriate categories or classes based on specificattributes or features to predict labels or classes of new data based on patternsobserved from previously trained data. …”
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  14. 14
    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH

    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

    Published 2005
    “…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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  15. 15
    Mutable composite firefly algorithm for gene selection in microarray based cancer classification

    Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

    Published 2022
    “…A computational approach for gene selection based on microarray data analysis has been applied in many cancer classification problems. …”
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  16. 16
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
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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
    Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image

    Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2014
    “…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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  19. 19
    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…The main objective of this research is to enhance the classification performance of the neural network-based bearing fault diagnostic module particularly when the input data has unpredictable variations compared to the training data under various working conditions. …”
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  20. 20
    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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