Search Results - (( java implementation during algorithm ) OR ( program data svm algorithm ))

Refine Results
  1. 1
  2. 2

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…Therefore, a new classifier based on genetic programming (GP) and support vector machine (SVM) is proposed in this thesis in order to solve the imbalanced classification problem without changing the data properties. …”
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    Kernel methods and support vector machines for handwriting recognition by Ahmad A.R., Khalid M., Yusof R.

    Published 2023
    “…SVM works by mapping training data for a classification task into a higher dimensional feature space using the kernel function and then finding a maximal margin hyperplane, which separates the mapped data. …”
    Conference paper
  4. 4

    Predicting uniaxial compressive strength using Support Vector Machine algorithm by Zakaria, Hafedz, Abdullah, Rini Asnida, Ismail, Amelia Ritahani, Amin, Mohd For

    Published 2019
    “…This paper presents the application of Support Vector Machine (SVM) algorithm to predict the UCS. An algorithm has been tested on a series of rock data using dry density and velocity parameters. …”
    Get full text
    Get full text
    Article
  5. 5

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
    Get full text
    Get full text
    Article
  6. 6
  7. 7
  8. 8

    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
  9. 9

    Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants by M, Irfan, N, Lukman, A. A, Alfauzi, J, Jumadi

    Published 2019
    “…By using each training data and testing data as many as 30 data. The results of the study were conducted, based on the accuracy of SVM, which was 82.33% and C4.5 89.29 %%. …”
    Get full text
    Get full text
    Conference or Workshop Item
  10. 10

    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
    Get full text
    Get full text
    Article
  11. 11

    Pairwise testing tools based on hill climbing algorithm (PTCA) by Lim, Seng Kee

    Published 2014
    “…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  12. 12

    Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

    Published 2018
    “…Five algorithms were employed to develop a classification model in determining the award of the scholarship, namely J48, SVM, NB, ANN and RT algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13

    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail by Ismail, Najihah

    Published 2021
    “…A Commercial Remote Sensing Technology (ENVI) was used and measured to improve and verify the performance of the Python programming-based picture classification by applying the same SVM algorithm and the tests indicated 95.0732% for an overall accuracy.…”
    Get full text
    Get full text
    Thesis
  14. 14

    Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

    Published 2011
    “…Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Face recognition using eigenfaces and smooth support vector machine by Mhd, Furqan

    Published 2011
    “…Support Vector Machine (SVM) is a new algorithm of data mining technique, recently received increasing popularity in machine learning community. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  16. 16
  17. 17

    Implementation Of SVM For Cascaded H-Bridge Multilevel Inverters Utilizing FPGA by Al-Jewari, Maher Abd Ibrahim

    Published 2019
    “…DT = 5 us. The data of switching signals for driving Insulated Gate Bipolar Transistors (IGBTSs) which are stored in MATLAB workspacs, are then used to be programmed in FPGA using a Quartus 11 software. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  18. 18
  19. 19
  20. 20

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceedings