Search Results - (( developing teacher classification algorithm ) OR ( java pattern classification algorithm ))

  • Showing 1 - 10 results of 10
Refine Results
  1. 1

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

    Published 2015
    “…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih by Hashim, Asman

    Published 2001
    “…Artificial Neural Network is one of the branches of Artificial Intelligence which is utilized for the purpose of classification and prediction based on data in hand. The purpose of the study is to develop a web-based self assessment information system that can be used to obtain a model for prediction of information technology competency among teacher trainees in teaching institutes. …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi by Habeebah Adamu , Kakudi

    Published 2019
    “…Therefore, the aim of this study is to propose and develop a novel non-clinical technique for the early risk quantification and classification of MetS refered to as genetically optimized Bayesian adaptive resonance theory mapping (GOBAM). …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Predicting STEM academic performance in secondary schools: data mining approach by Termedi @Termiji, Mohammad Izzuan, Ab. Jalil, Habibah

    Published 2019
    “…Three different data mining classification algorithms which are Decision Tree (DT), Artificial Neural Networks (ANN), and Naive Bayes (NB) will be used on the dataset. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  6. 6

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
    Get full text
    Get full text
    Thesis
  7. 7

    Al-Hams and Al-Jahr Sifaat evaluation using classification approach by Altalmas, Tareq, M., Ahmad, Salmiah, Sediono, Wahju, Nik Hashim, Nik Nur Wahidah, Embong, Abd Halim, Hassan, Surul Shahbudin

    Published 2021
    “…As a part of the automated system’s developed, therefore, in this paper, a classification approach is introduced to develop a classification model that can classify the Quranic letters to its first pair of Sifaat with opposites (Al-Hams and Al-Jahr). …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  8. 8
  9. 9

    Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining by Termedi @ Termiji, Mohammad Izzuan

    Published 2023
    “…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
    Get full text
    Get full text
    Thesis
  10. 10

    Identifying the correct articulation point of a Quranic letters of the throat (al-halqu) makhraj by Othman, Ahmad Al Baqir, Ahmad, Salmiah, Badron, Khairayu, Altalmas, Tareq M. K.

    Published 2023
    “…Data was trained using an improved deep learning Convolutional Neural Network (CNN) classification model. Results shows that the algorithm was able to detect the letters produced at throat area, which are also known as Izhar Halqi letters. …”
    Get full text
    Get full text
    Get full text
    Article