Search Results - (( bayesian classification problem algorithm ) OR ( program implementation mining algorithm ))

Refine Results
  1. 1

    A Comparison Between Levenberg-Marquardt (LM) Intelligent System And Bayesian Regularization (BR) Intelligent System For Flow Regime Classification by Sa'ad, Mohamad Iqbal

    Published 2006
    “…The purpose of this project is to study the performance, leaning time and, output of Levenberg-Marquardt (LM) intelligent system and Bayesian Regularization (BR) intelligent system through a classification problem. …”
    Get full text
    Get full text
    Monograph
  2. 2

    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…In this system a Bayesian algorithm was used in order to implement the system. …”
    Get full text
    Get full text
    Thesis
  3. 3
  4. 4

    Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

    Published 2024
    “…The class imbalance makes estimating building damage grades difficult, emphasizing the necessity for careful modeling. Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
    Get full text
    Get full text
    Article
  5. 5

    Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

    Published 2009
    “…Bayesian classification and decision making are based on probability theory and choosing the most probable or the lowest risk. …”
    Get full text
    Get full text
    Thesis
  6. 6

    A comparative study in classification techniques for unsupervised record linkage model by Ektefa, Mohammadreza, Sidi, Fatimah, Ibrahim, Hamidah, A. Jabar, Marzanah, Memar, Sara

    Published 2011
    “…Duplicate detection and classification of records in two real world datasets, namely Cora and Restaurant is experimented by Support Vector Machines, Naïve Bayes, Decision Tree and Bayesian Networks which are regarded as some prominent classification techniques. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

    Published 2021
    “…Machine learning is an implementation of artificial intelligence (Al) that allows systems to learn and build on knowledge without being directly programmed automatically. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Robust Pornography Classification Solving the Image Size Variation Problem Based on Multi-Agent Learning by Zaidan, A.A., Karim, H.A., Ahmad, N.N., Zaidan, B.B., Mat Kiah, M.L.

    Published 2015
    “…The classification of pornographic images was made more robust to the variation of images despite size engineering problems. …”
    Get full text
    Get full text
    Article
  9. 9
  10. 10

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

    Published 2004
    “…Finding a good classification algorithm is an important component of many data mining projects. …”
    Get full text
    Get full text
    Thesis
  11. 11

    Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data by Qaedi, Kasyful, Abdullah, Mardina, Yusof, Khairul Adib, Hayakawa, Masashi, Zulhamidi, Nur Fatin Irdina

    Published 2025
    “…The extracted features were the input for AutoML, an automatic algorithm selection that was measured by Bayesian Optimization algorithm to select the best performance model. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure by Asmai, S. A.

    Published 2014
    “…The other 40% of the dataset is used to test generated rules. A simple program of C++ is implemented using Microsoft Visual Studio to test generated rules until accuracy of performance is obtained. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  14. 14
  15. 15
  16. 16

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…In this research, a hand-written character recognition model are implemented in C++ programming with ability to classify digits 0, 1, 2, and 3. …”
    Get full text
    Get full text
    Thesis
  17. 17
  18. 18

    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

    Published 2025
    “…No previous study has investigated Orange mining tool as visual programming approach in analysing hyperspectral reflectance data, especially in crop disease detection. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia by Ajibola, Lamidi-Sarumoh Alaba

    Published 2019
    “…Dengue viral infection is a global health problem that has spread exponentially across the tropical and sub-tropical regions of the world. …”
    Get full text
    Get full text
    Thesis
  20. 20

    Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan by Mohd Hanis, Rani, Abdullah, Embong

    Published 2013
    “…The objective was to identify and implement the most accurate algorithm for the KPTM dataset and to come up with a good prediction model using decision tree technique. …”
    Get full text
    Get full text
    Conference or Workshop Item