Search Results - (( parameter optimization based algorithm ) OR ( learning classification tree algorithm ))

Refine Results
  1. 1

    Intrusion Detection Systems, Issues, Challenges, and Needs by Aljanabi, Mohammad, Mohd Arfian, Ismail, Ali, Ahmed Hussein

    Published 2021
    “…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

    Published 2019
    “…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…The segmentation process was optimized using Fuzzy-based Segmentation Parameter. …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
    Get full text
    Get full text
    Thesis
  5. 5

    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
  6. 6

    Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging by Mohd Ali, Maimunah

    Published 2022
    “…Several machine learning algorithms including linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbour, support vector machine, decision tree, and Naïve Bayes were applied for the classification of pineapple varieties. …”
    Get full text
    Get full text
    Thesis
  7. 7
  8. 8

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

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
    Get full text
    Get full text
    Thesis
  9. 9

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…One of the most powerful machine learning methods to handle classification problems is the decision tree. …”
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13
  14. 14

    Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

    Published 2023
    “…The performance of SVM can be affected by hyperparameters, which are kernel scale and known as gamma and regularization parameters (C). A metaheuristic algorithm is introduced to optimise the hyperparameters. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2021
    “…FID3 algorithm combined the fuzzy system and decision tree techniques with ID3 algorithm as the decision tree learning. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Accuracy and performance analysis for classification algorithms based on biomedical datasets by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Khubrani, Mousa, Fakhreldin, Mohammoud

    Published 2021
    “…Trees based Decision Tree (ID3) algorithm, Bayesian Theorem based Hidden Naïve Bayes (HNB) algorithm. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  17. 17

    Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

    Published 2023
    “…At the early infection stage, it is very difficult to diagnose the disease because infected trees do not exhibit any symptoms. Thus, this study was carried out to investigate the potential application of spectroscopic technology and machine learning algorithms to classify severity level of infected trees at early stage based on spectral data. …”
    Get full text
    Get full text
    Get full text
    Book Section
  18. 18
  19. 19

    Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

    Published 2020
    “…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  20. 20