Search Results - (( web application method algorithm ) OR ( learning classification using algorithm ))

Refine Results
  1. 1

    K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

    Published 2025
    “…This research presents a two-phase phishing detection system by employing unsupervised feature selection and supervised classification. In the first phase, the best set of features is identified by the Genetic algorithm and is utilised by the K-means clustering algorithm to divide the dataset into groups with similar traits. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

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

    Published 2008
    “…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
    Get full text
    Get full text
    Article
  3. 3

    A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

    Published 2023
    “…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
    Get full text
    Get full text
    Article
  4. 4

    Phishing image spam classification research trends: Survey and open issues by John Abari, Ovye, Mohd Sani, Nor Fazlida, Khalid, Fatimah, Mohd Yunus Bin Sharum, Mohd Yunus, Mohd Ariffin, Noor Afiza

    Published 2020
    “…Low-level and image metadata are the most widely used features set. The methods of image spam classification as identified in this study are supervised machine learning, unsupervised machine learning, semi-supervised machine learning, content-based and statistical learning. …”
    Get full text
    Get full text
    Article
  5. 5

    Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart... by Hamza H. M. , Altarturi

    Published 2023
    “…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
    Get full text
    Get full text
    Get full text
    Thesis
  6. 6

    A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

    Published 2023
    “…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    Banana recognition system using convolutional neural network / Mohamad Shafiq Rosli by Rosli, Mohamad Shafiq

    Published 2021
    “…With the rise of mobile technology and internet access, recent development in machine learning have designed many algorithms to solve diverse human problems. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Visual codebook analysis in image understanding / Hoo Wai Lam by Hoo, Wai Lam

    Published 2015
    “…State-of-the-art approaches often used attributes as the zero-shot learning solution. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Analysis On QOS Parameters To Predict Http Response by A.Rahman, Khairulnizam

    Published 2017
    “…Therefore, the real live world web service label data uses to evaluate the focus parameters using classification machine learning algorithms to process the data. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11

    How can unmanned aerial vehicles be used for detecting weeds in agricultural fields? by Mohidem, Nur Adibah, Che’Ya, Nik Norasma, Juraimi, Abdul Shukor, Fazlil Ilahi, Wan Fazilah, Mohd Roslim, Muhammad Huzaifah, Sulaiman, Nursyazyla, Saberioon, Mohammadmehdi, Mohd Noor, Nisfariza Maris

    Published 2021
    “…Most of the weed images were captured using red, green, and blue (RGB) camera, i.e., 48.28% and main classification algorithm was machine learning techniques, i.e., 47.90%. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12
  13. 13

    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. …”
    Get full text
    Get full text
    Thesis
  14. 14

    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. …”
    Get full text
    Get full text
    Get full text
    Final Year Project Report / IMRAD
  15. 15

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    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. …”
    Get full text
    Get full text
    Thesis
  17. 17

    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. …”
    Get full text
    Get full text
    Final Year Project
  18. 18

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  20. 20

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis