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  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
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  2. 2
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  4. 4
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  5. 5
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  6. 6
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  7. 7
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  8. 8
    DESIGN AND DEVELOPMENT OF ANDROID-BASED LEARNING MEDIA FOR LEARNING ALGORITHM AND DATA STRUCTURE

    DESIGN AND DEVELOPMENT OF ANDROID-BASED LEARNING MEDIA FOR LEARNING ALGORITHM AND DATA STRUCTURE by Rosyid Ridlo, Al Hakim, Rianti Y., Kisworini, Aditia P., Hamid, Agung, Pangestu, Ariep, Jaenul, Yanuar Zulardiansyah, Arief

    Published 2021
    “…One of the learning techniques is in the form of algorithms and data structures. …”
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    Proceeding
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  9. 9
    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
    “…As for classification, researchers have used semi-supervised learning for extreme learning machine (ELM), where they have exploited both the labeled and unlabeled data in order to boost the learning performances. …”
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  10. 10
    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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  11. 11
    Impact learning: A learning method from feature's impact and competition

    Impact learning: A learning method from feature's impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
    “…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
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  12. 12
    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

    Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection by Tubishat, Mohammad, Idris, Norisma, Shuib, Liyana, Abushariah, Mohammad A.M., Mirjalili, Seyedali

    Published 2020
    “…These problems will occur because these fields are mainly used machine learning classifiers. However, machine learning accuracy is affected by the noisy and irrelevant features. …”
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  13. 13
    Octane number prediction for gasoline blends using convolution neural network / Zhu Yue

    Octane number prediction for gasoline blends using convolution neural network / Zhu Yue by Zhu , Yue

    Published 2021
    “…Machine performance learning models depend to a large extant to the data quality used train the model. …”
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  14. 14
    Impact learning : A learning method from feature’s impact and competition

    Impact learning : A learning method from feature’s impact and competition by Prottasha, Nusrat Jahan, Murad, Saydul Akbar, Abu Jafar, Md Muzahid, Rana, Masud, Kowsher, Md, Adhikary, Apurba, Biswas, Sujit, Bairagi, Anupam Kumar

    Published 2023
    “…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
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  15. 15
    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA

    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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  16. 16
    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data

    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

    Published 2018
    “…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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  17. 17
    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat

    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

    Published 2022
    “…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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  18. 18
    Case Slicing Technique for Feature Selection

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

    Published 2004
    “…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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  19. 19
    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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  20. 20
    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data

    Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

    Published 2025
    “…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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