Search Results - (( program bayes classification algorithm ) OR ( java application optimization algorithm ))

Refine Results
  1. 1

    Classification Algorithms to Determine Students’ Specialization in a Higher Education Institution by Tri Basuki, Kurniawan, Indah, Hidayanti

    Published 2023
    “…After that, we looked at how Python programming classification algorithms like Support Vector Machine (SVM), Naïve Bayes, Random Forest, and Decision Tree performed in classifying the areas of specialization of the students. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2
  3. 3
  4. 4

    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
  5. 5

    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

    Published 2014
    “…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
    Get full text
    Get full text
    Get full text
    Article
  6. 6
  7. 7

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8
  9. 9

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
    Get full text
    Get full text
    Final Year Project
  10. 10
  11. 11
  12. 12
  13. 13

    Towards a better feature subset selection approach by Shiba, Omar A. A.

    Published 2010
    “…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  14. 14
  15. 15

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

    Published 2021
    “…There are many machines learning types and classification techniques have widely used nowadays such as Support Vector Machine, K-Nearest Neighbors, Neural Network and Naïve-Bayes Classifier are defined and studied. …”
    Get full text
    Get full text
    Thesis
  16. 16
  17. 17

    A review on sentiment analysis model Chinese Weibo text by Dawei Wang, Rayner Alfred

    Published 2020
    “…For traditional machine learning, there are 2 mainly aspects of innovation: Simultaneous classifier (Adoboost+SVM) and Improvement of classical classification algorithm. One worth noted is that the performance of the some improve classifier (SVM, P Naïve Bayes) has not been verified in Chinese Weibo classification. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceedings
  18. 18

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
    Get full text
    Get full text
    Thesis
  19. 19
  20. 20

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
    Get full text
    Get full text
    Thesis