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  1. 1
    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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  2. 2
    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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  3. 3
    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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  4. 4
    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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  5. 5
    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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  6. 6
    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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  7. 7
    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction

    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
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  8. 8
    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
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  9. 9
    Training functional link neural network with ant lion optimizer

    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
    “…This paper proposed the implementation of Ant Lion Algorithm as learning algorithm to train the FLNN for classification tasks. …”
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  10. 10
    Dynamic training rate for backpropagation learning algorithm

    Dynamic training rate for backpropagation learning algorithm by Al-Duais, M. S., Yaakub, Abdul Razak, Yusoff, Nooraini

    Published 2013
    “…In this paper, we created a dynamic function training rate for the Back propagation learning algorithm to avoid the local minimum and to speed up training.The Back propagation with dynamic training rate (BPDR) algorithm uses the sigmoid function.The 2-dimensional XOR problem and iris data were used as benchmarks to test the effects of the dynamic training rate formulated in this paper.The results of these experiments demonstrate that the BPDR algorithm is advantageous with regards to both generalization performance and training speed. …”
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  11. 11
    Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm

    Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm by Fatma Susilawati, Mohamad, Mumtazimah, Mohamad, Sarhan, AlDuais

    Published 2020
    “…From the experimental results, the dynamic algorithm provides superior performance in terms of faster training with highest accuracy training compared to the manual algorithm. …”
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  12. 12
    Fast sequential learning methods on RBF-network using decomposed training algorithms

    Fast sequential learning methods on RBF-network using decomposed training algorithms by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2004
    “…This work investigates novel sequential learning methods applied on a decomposed form of training algorithms using radial basis function (RBF) network. …”
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  13. 13
    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification

    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong S.Y., Yap K.S., Yap H.J., Tan S.C.

    Published 2023
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  14. 14
    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin

    Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

    Published 2022
    “…The Windows malware dataset has been trained and tested by these three machine learning algorithms to get the percentage detection accuracy. …”
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  15. 15
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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  16. 16
    CLASSIFICATION OF BEARING FAULTS USING EXTREME LEARNING MACHINE ALGORITHMS

    CLASSIFICATION OF BEARING FAULTS USING EXTREME LEARNING MACHINE ALGORITHMS by TEH, CHOON KEONG

    Published 2017
    “…Therefore, this project introduces three learning algorithms which are Extreme Learning Machine (ELM), Finite Impulse Response Extreme Learning Machine (FIR-ELM) and Discrete Fourier Transform Extreme Learning Machine (DFT-ELM) to improve the bearing fault diagnosis accuracy and shorten the time used to train and test the neural network.…”
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  17. 17
    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification

    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong, S.Y., Yap, K.S., Yap, H.J., Tan, S.C.

    Published 2015
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  18. 18
    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
    “…The research work also investigates several recursive algorithms including recursive Kalman filter (RKF) and extended Kalman filter (EKF) using extreme learning machine (ELM) and hybrid linear/nonlinear training technique by incorporating the fiee derivative concept. …”
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  19. 19
    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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  20. 20
    Memory efficient BFGS neural-network learning algorithms using MLP-network: a survey

    Memory efficient BFGS neural-network learning algorithms using MLP-network: a survey by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2004
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