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  1. 1
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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  2. 2
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
    “…Due to the importance of blood vessel detection in many medical tools and the increasing demand for portable diagnosis equipment, fast blood vessel detection algorithm in a standalone and portable device is very important. …”
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  3. 3
    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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  4. 4
    Phylogenetic tree classification system using machine learning algorithm

    Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

    Published 2015
    “…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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    Final Year Project Report / IMRAD
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  5. 5
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    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
    “…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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  6. 6
    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
    “…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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  7. 7
    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms

    Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

    Published 2021
    “…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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    Final Year Project
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  8. 8
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…The goal of this paper is to evaluate the deep learning algorithm for people placed in the Autism Spectrum Disorder (ASD) classification. …”
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  9. 9
    An approach for cross-site scripting detection and removal based on genetic algorithms.

    An approach for cross-site scripting detection and removal based on genetic algorithms. by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia

    Published 2014
    “…In this paper, we propose to explore an approach based on genetic algorithms that will be able to detect and remove cross-site scripting vulnerabilities from the source code before an application is deployed. …”
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  10. 10
    Functional link neural network with modified bee-firefly learning algorithm for classification task

    Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

    Published 2016
    “…The single layer property of FLNN also make the learning algorithm used less complicated compared to MLP network. …”
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  11. 11
    Real-Time Video Processing Using Native Programming on Android Platform

    Real-Time Video Processing Using Native Programming on Android Platform by Saipullah, Khairul Muzzammil

    Published 2012
    “…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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  12. 12
    An improved algorithm for iris classification by using support vector machine and binary random machine learning

    An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

    Published 2018
    “…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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  13. 13
    Waste management using machine learning and deep learning algorithms

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…So, we are proposing an automated waste classification problem utilizing Machine Learning and Deep Learning algorithms. …”
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  14. 14
    Using KNN algorithm for classification of textual documents

    Using KNN algorithm for classification of textual documents by Moldagulova A., Sulaiman R.B.

    Published 2023
    Conference Paper
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  15. 15
    Fitness value based evolution algorithm approach for text steganalysis model

    Fitness value based evolution algorithm approach for text steganalysis model by Din, Roshidi, Samsudin, Azman, Tuan Muda, Tuan Zalizam, Lertkrai, P., Amphawan, Angela, Omar, Mohd Nizam

    Published 2013
    “…In this paper, we present a new alternative method for text steganalysis based on an evolution algorithm, implemented using the Java Evolution Algorithms Package (JEAP).The main objective of this paper is to detect the existence of hidden messages ased on fitness values of a text description.It is found that the detection performance has been influenced by two groups of fitness values which are good fitness value and bad fitness value. …”
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  16. 16
    An automated strabismus classification using machine learning algorithm for binocular vision management system

    An automated strabismus classification using machine learning algorithm for binocular vision management system by Rohismadi, Muhammad Amirul Isyraf, Mat Raffei, Anis Farihan, Zulkifli, Nor Saradatul Akmar, Ithnin, Mohd. Hafidz, Othman, Shah Farez

    Published 2023
    “…To overcome these limitations, a machine learning algorithm, which is a case-based reasoning, is developed to automate the strabismus classification. …”
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    Proceeding Paper
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  17. 17
    Performance comparison of CNN and LSTM algorithms for arrhythmia classification

    Performance comparison of CNN and LSTM algorithms for arrhythmia classification by Hassan, S.U., Zahid, M.S.M., Husain, K.

    Published 2020
    “…Among the existing deep learning model, convolutional neural network (CNN) and long short-term memory (LSTM) algorithms are extensively used for arrhythmia classification. …”
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  18. 18
    Cross-site scripting detection based on an enhanced genetic algorithm

    Cross-site scripting detection based on an enhanced genetic algorithm by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia Indriaty

    Published 2015
    “…In this paper, we propose to explore an approach based on genetic algorithms that will be able to detect cross-site scripting vulnerabilities in the source code before an application is deployed. …”
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  19. 19
    A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification

    A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

    Published 2024
    “…For machine learning, SVM is a very good classification model. …”
    Conference Paper
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  20. 20
    Evaluation of the Transfer Learning Models in Wafer Defects Classification

    Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

    Published 2022
    “…The key metrics for the evaluation are classification accuracy, classification precision and classification recall. 855 images were used to train and test the algorithms. …”
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