Search Results - (( program during classification algorithm ) OR ( java application mining algorithm ))

Refine Results
  1. 1
  2. 2
  3. 3

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Software Classification Using Structure-Based Descriptors by Ramadan, Qusai Hussein

    Published 2009
    “…Based on the undertaken experiment, the IBK algorithm is noted to generate the highest classification accuracy (74.8%) compared to several other algorithms provided in the Weka tool. …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
    Get full text
    Get full text
    Thesis
  6. 6

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  7. 7

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  8. 8
  9. 9

    Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment by Al-Doski, Jwan M. Mohammed

    Published 2013
    “…In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq. …”
    Get full text
    Get full text
    Thesis
  10. 10

    An optimal mesh algorithm for remote protein homology detection by M. Abdullah, Firdaus, M. Othman, Razib, Kasim, Shahreen, Hashim, Rathiah, Hassan, Rohayanti, Asmuni, Hishammuddin, Taliba, Jumail

    Published 2011
    “…This paper further presents the best combinations of multiple alignment and classification programs to be chosen. This paper also improves the quality of the multiple alignments via integration of a refinement algorithm. …”
    Get full text
    Get full text
    Article
  11. 11

    Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.] by Anang, N., Jailani, R., Mustafah, N., Manaf, H.

    Published 2018
    “…This paper presents the gait pattern classification between 3 groups which are control, stroke only and stroke with Peripheral Neuropathy (SPN) using k-Nearest Neighbors (kNN) algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12
  13. 13

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

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
    Get full text
    Get full text
    Thesis
  14. 14

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…The problem occurs during the transition from learning fundamental programming language concept to OOP concept. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

    Published 2021
    “…The methodology starts with literature comprehension studies on the computation pitfalls and existed augmentation studies of Simplex algorithm. Then, followed by concept development which consists of concept extraction, computation stages classification and algorithms integration. …”
    Get full text
    Get full text
    Get full text
    Thesis
  17. 17
  18. 18

    Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms by Bakar, Abubakar Diwani

    Published 2016
    “…The study proposes the use of software metric thresholds in the classification process during the GA representation. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Simulation on Emotion Recognition for Autism Therapy by Adzmi, Muhammad Azrin

    Published 2017
    “…This paper mainly focusing on the simulation of emotion recognition software based on the Local Binary Pattern (LBP) algorithm to extract the features from the image. The program will be used by the therapist during therapy session with the autism child in order to create more exciting environment for them to learn about the classification of basic human emotions with the help of human-computer interaction. …”
    Get full text
    Get full text
    Final Year Project
  20. 20

    An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection by Shing, Chiang Tan, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Lim, Pey, Yun Goh, Chee, Peng Lim

    Published 2023
    “…The stacked ensemble method uses several heterogeneous deep neural networks as the base learners. During the training and optimization process, these base learners adopt a hybrid BP and Particle Swarm Optimization algorithm to combine both local and global optimization capabilities for identifying optimal features and improving the classification performance. …”
    Get full text
    Get full text
    Get full text
    Article