Search Results - (( program implementation mining algorithm ) OR ( parametric classification based algorithm ))

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  1. 1
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
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  2. 2
    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…The second stage involved assessing the spatial resolution effect through utilizing Landsat 8 (30 m) and Sentinel (10 m) data on LCM accuracy using SVM, K-Nearest Neighbor (K-NN), Random Forest (RF), and Neural Network (NN) algorithms. Based on the concluding overall analysis, the classification accuracy derived from Sentinel 2 imagery utilizing SVM and RF, Landsat 8 applying SVM donated higher than other methods of classification. …”
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  3. 3
    Nearest neighbour group-based classification

    Nearest neighbour group-based classification by Samsudin, Noor A., Bradley, Andrew P.

    Published 2010
    “…In this paper, we extend three variants of the nearest neighbour algorithm to develop a number of non-parametric group-based classification techniques. …”
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  4. 4
    Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak

    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. …”
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  5. 5
    Validation on an enhanced dendrite cell algorithm using statistical analysis

    Validation on an enhanced dendrite cell algorithm using statistical analysis by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Abd Wahab, Mohd Helmy

    Published 2017
    “…In this study, we evaluated the performance of the enhanced algorithm called dendrite cell algorithm using sensitivity, specificity, false positive rate, and accuracy and validated the result using parametric and non parametric statistical significant tests. …”
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  6. 6
    Data mining techniques for transformer failure prediction model: A systematic literature review

    Data mining techniques for transformer failure prediction model: A systematic literature review by Ravi N.N., Mohd Drus S., Krishnan P.S.

    Published 2023
    Conference Paper
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  7. 7
    Case Slicing Technique for Feature Selection

    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. …”
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  8. 8
    Segmentation of masses from breast ultrasound images using parametric active contour algorithm

    Segmentation of masses from breast ultrasound images using parametric active contour algorithm by Jumaat, Abdul Kadir, Wan Abdul Rahman, Wan Eny Zarina, Ibrahim, Arsmah, Mahmud, Rozi

    Published 2010
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  9. 9
    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…The experimental results are also thoroughly evaluated and verified via non-parametric statistical analysis. Based on the obtained experimental results, the OGC, DPSO, and VDEO frameworks achieved an average enhancement up to 24.36%, 9.38%, and 11.98% of classification accuracy, respectively. …”
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  10. 10
    Enhancing predictive crime mapping model using association rule mining for geographical and demographic structure

    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. …”
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  11. 11
    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
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  12. 12
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    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. …”
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  13. 13
    Novel voice activity detection based on cepstrum moments

    Novel voice activity detection based on cepstrum moments by Farzan, Ali, Nourmohammadi, Ali, Mashohor, Syamsiah, Sadra, Sarvin

    Published 2010
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  14. 14
    Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining

    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. …”
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  15. 15
    Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan

    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. …”
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  16. 16
    Propositional satisfiability method in rough classification modeling for data mining

    Propositional satisfiability method in rough classification modeling for data mining by Abu Bakar, Azuraliza

    Published 2002
    “…Two models, Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) to represent the minimal reduct computation problem were proposed. …”
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  17. 17
    Sentiment analysis using clonal selection algorithm for Twitter’s data / Fatimah Mamat

    Sentiment analysis using clonal selection algorithm for Twitter’s data / Fatimah Mamat by Mamat, Fatimah

    Published 2012
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  18. 18
    The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop

    The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop by Kerdprasop, Nittaya, Kerdprasop, Kittisak

    Published 2014
    “…These representatives are subsequently used in the main process of frequent pattern mining. Our designed algorithm had been implemented with the Erlang language, which is the functional programming paradigm with inherent support for pattern matching. …”
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  19. 19
    Web page design for electronic commerce / Lee Fong Wai

    Web page design for electronic commerce / Lee Fong Wai by Lee , Fong Wai

    Published 2003
    “…The sixth part covers the system implementation that involved the transformation of modules and algorithm into implementable commands by using the specified programming languages. …”
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  20. 20
    Problem restructuring in interger programming for reduct searching

    Problem restructuring in interger programming for reduct searching by Ungku Chulan, Ungku Azmi Iskandar

    Published 2003
    “…They can describe the whole information system when implementing discernment. In effect, they are very useful in generating rules when solving the classification problem that is inherent in data mining. …”
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