Search Results - (( data classification technique algorithm ) OR ( binary classification methods algorithm ))

Refine Results
  1. 1

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

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2021
    “…Text classification is a popular method in data mining. It is utilized to get valuable information from the vast quantity of data. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  3. 3

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

    Published 2018
    “…The second objective is to conduct a supervised and binary ensemble machine learning technique for classification. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

    Published 2010
    “…The experimental results show that Naive-Bayes classifier with web text extraction algorithm proves to be the best method for web text classification.…”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

    Published 2014
    “…The reduction method contains two techniques, namely features reduction and data reduction which are commonly applied to a classification problem. …”
    Get full text
    Get full text
    Conference or Workshop Item
  6. 6

    Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification by Al-Tashi, Q., Rais, H.M., Abdulkadir, S.J., Mirjalili, S.

    Published 2020
    “…In addition, to examine the efficiency of the proposed method, two recent algorithms namely: Whale Optimization algorithm (WAO) and Dragonfly Algorithm (DA) are implemented for comparison. …”
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    Hybrid binary whale with harris hawks for feature selection by Alwajih, R., Abdulkadir, S.J., Al Hussian, H., Aziz, N., Al-Tashi, Q., Mirjalili, S., Alqushaibi, A.

    Published 2022
    “…As a result, feature selection is offered as a method for eliminating unwanted characteristics. This study introduces the BWOAHHO memetic technique, which combines the binary hybrid Whale Optimization Algorithm (WOA) with Harris Hawks Optimization (HHO). …”
    Get full text
    Get full text
    Article
  8. 8

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
    Get full text
    Get full text
    Thesis
  9. 9

    A Steganalysis Classification Algorithm Based on Distinctive Texture Features by Hammad B.T., Ahmed I.T., Jamil N.

    Published 2023
    “…Due to their enormous feature vector dimension, which requires more time to calculate, the performance of most existing image steganalysis classification (ISC) techniques is still restricted. Therefore, in this research, we present a steganalysis classification method based on one of the texture features chosen, such as segmentation-based fractal texture analysis (SFTA), local binary pattern (LBP), and gray-level co-occurrence matrix (GLCM). …”
    Article
  10. 10

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…In this paper, an improved method for intrusion detection for binary classification was presented and discussed in detail. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Rao-SVM machine learning algorithm for intrusion detection system by Abd, Shamis N., Alsajri, Mohammad, Ibraheem, Hind Raad

    Published 2020
    “…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

    Published 2025
    “…Comparative evaluations with existing dropout methods demonstrated the superior performance of the proposed technique, particularly when applied within the Algorithm Adaptation framework using DNNs. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Enhancement of new smooth support vector machines for classification problems by Santi Wulan, Purnami

    Published 2011
    “…The results of this study showed that MKS-SSVM was effective to diagnose medical dataset and this is promising results compared to the previously reported results. SSVM algorithms are developed for binary classification. …”
    Get full text
    Get full text
    Thesis
  14. 14

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

    Published 2008
    “…The design of our method is a kind of One-Against-All multi classification technique to solve the traditional binary classifier in SVM.…”
    Get full text
    Get full text
    Article
  15. 15

    Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

    Published 2015
    “…These classification algorithms are trained using the features extracted from the patient data in order for them to learn the relationship between the features and the end-result (FLD present or absent). …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16
  17. 17

    Global and local clustering soft assignment for intrusion detection system: a comparative study by Mohd Rizal Kadis, Azizi Abdullah

    Published 2017
    “…Machine Learning algorithm such as unsupervised learning and supervised learning is capable to solve the problem of classification in IDS. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    Feature clustering for pso-based feature construction on high-dimensional data by Swesi, Idheba Mohamad Ali Omer, Abu Bakar, Azuraliza

    Published 2019
    “…Hence, the ClusPSOFC method is effective for feature construction in the classification of high dimensional data.…”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Segmentation Assisted Object Distinction For Direct Volume Rendering by Irani, Arash Azim Zadeh

    Published 2013
    “…A set of image processing techniques are creatively employed in the design of K-means based hybrid segmentation algorithm.…”
    Get full text
    Get full text
    Thesis
  20. 20

    Enhanced extreme learning machine for general regression and classification tasks by Mahmood, Saif F

    Published 2020
    “…The proposed FASTA-ELM replaces the analytical step usually solved by SVD with an approximate solution through proximal gradient method, which dramatically speeds up the training time and improves the generalization ability in classification task. …”
    Get full text
    Get full text
    Thesis