Search Results - (( using function learning algorithm ) OR ( text classification based algorithm ))

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  1. 1

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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    Article
  2. 2

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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    Thesis
  3. 3
  4. 4

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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    Academic Exercise
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  6. 6

    Development of machine learning-based algorithm to determine the condition in transformer oil by Mohsen Al-Katheri, Hussein Hasan

    Published 2021
    “…Classification learning app used to train DGA data divided into three categories fault, Not determined (N/D) and stray gassing. …”
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    Thesis
  7. 7

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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    Thesis
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  9. 9

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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    Thesis
  10. 10

    Odour based human identification and classification using neural networks by Ahmed Qusay Sabri, Rayner Alfred

    Published 2019
    “…The unsurpassed framework for algorithm learning to be used for human identification can be back propagation learning algorithm named the Levenberg-Marquardt. …”
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  11. 11

    New Instances Classification Framework On Quran Ontology Applied To Question Answering System by Utomo, Fandy Setyo, Suryana, Nanna, Azmi, Mohd Sanusi

    Published 2019
    “…The existing classification approach used machine learning: Backpropagation Neural Network. …”
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  12. 12

    Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

    Published 2008
    “…Nowadays more researchers use three type of approaches namely, Rule-base NER, Machine Learning-base NER and Hybrid NER to identify names. …”
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    Article
  13. 13

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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    Thesis
  14. 14

    Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain by Mohamad Zain, Muhammad Asyraf

    Published 2020
    “…To counter this problem, a system has been proposed to detect the hand gesture using one of the machine learning technique which is Support Vector Machine (SVM) Algorithm. …”
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    Thesis
  15. 15

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…Data analysis, data reduction, approxi mate classification, machine learning, and discovery of pattern in data are functions performed by a rough sets analysis. …”
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    Thesis
  16. 16

    Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals by Neili, Zakaria, Sundaraj, Kenneth

    Published 2025
    “…Breathing sounds from the ICBHI and KAUHS databases are analyzed, where three key intrinsic mode functions (IMFs) are extracted using VMD and subsequently converted into CQT-based time-frequency representations. …”
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  17. 17

    Context aware app recommendation using email semantic analysis by Tang, Zi Cong

    Published 2019
    “…Then the da ta will go through the machine learning algorithm to perform predict and provide a recommendation that suitable for the content.…”
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    Final Year Project / Dissertation / Thesis
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    Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak by Abd Razak, Hana'

    Published 2020
    “…Convolution Neural Network (CNN) using deep learning algorithm is chosen in identifying frequency of movement and execution time of housebreaking crime. …”
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    Thesis
  19. 19

    An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

    Published 2020
    “…Although activation functions are important for MLP to learn but for nonlinear complex functional mappings it has complicated calculation which reduces the accuracy of classification. …”
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    Thesis
  20. 20

    Smart fall detection by enhanced SVM with fuzzy logic membership function by Harum, Norharyati, Khalil, Mohamad Kchouri, Hazimeh, Hussein, Obeid, Ali

    Published 2023
    “…In addition, they use thresholds to identify falls based on artificial experiences or machine learning (ML) algorithms. …”
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