Search Results - (( java implementation clustering algorithm ) OR ( program class learning algorithm ))

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  1. 1

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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    Thesis
  2. 2

    The impact of virtual reality on programming algorithm courses on student learning outcomes by Dewi, Ika Parma, Ambiyar, Effendi, Hansi, Giatman, Muhammad, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

    Published 2024
    “…This study aims to determine the impact of VR compared to traditional learning in improving student learning outcomes on programming algorithm materials. …”
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    Article
  3. 3

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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    Thesis
  4. 4

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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    Final Year Project
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    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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    Final Year Project / Dissertation / Thesis
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    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
    “…In supervised learning, class imbalanced data set is a state where the class distribution is not uniform among the classes. …”
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    Thesis
  9. 9

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
    “…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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    Conference or Workshop Item
  10. 10

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

    Published 2004
    “…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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    Thesis
  11. 11

    Analysis Of Personal Protective Equipment Classification Method Using Deep Learning by Siti Zahrah Nur Ain, Silopung

    Published 2022
    “…To avoid a tedious work in manually checking whether workers wear PPE or not, an automatic PPE classifier is constructed by utilizing a deep learning algorithm called Convolutional Neural Network (CNN). …”
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    Undergraduates Project Papers
  12. 12

    Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi by Mohd Pauzi, Mohd Farhan

    Published 2022
    “…Therefore, this study aims to detect the existence of "in-car-abandoned children" using deep learning algorithm. A set of children images model captured and then classified into two (2) classes; children and no-children via Convolutional Neural Network (CNN) classifier. …”
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    Thesis
  13. 13

    Poverty Classification of Central Perak Population Using Machine Learning by P.Rajendran, Kumaran

    Published 2019
    “…In this study, back propagation algorithm and other machine learning algorithm will be used to build models via anaconda using python programming language that can classify each poor household appropriate their poverty status. …”
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    Final Year Project
  14. 14

    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. …”
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    Thesis
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    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 paper focuses on prediction of student learning performance in object oriented programming course using data mining technique based on a dataset obtained from Kolej Poly-Tech Mara (KPTM), Kuantan. …”
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    Conference or Workshop Item
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    Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

    Published 2011
    “…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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    Thesis
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    An efficient and effective case classification method based on slicing by Shiba, Omar A. A., Sulaiman, Md. Nasir, Mamat, Ali, Ahmad, Fatimah

    Published 2006
    “…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
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    Article
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    Path Following Using A Learning Neural Network by NHH , Mohamad Hanif

    Published 2004
    “…The class of learning (whether good or bad) of the neural controllers is evaluated from the obtained percentage of average weight change, maximum path and yaw attitude angle errors as well as the maximum steering wheel angle. …”
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    Final Year Project
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