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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  2. 2
    Study and Implementation of Data Mining in Urban Gardening

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

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  5. 5
    Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study

    Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study by Sim, Doreen Ying Ying, Teh, Chee Siong, Ahmad Izuanuddin, Ismail

    Published 2020
    “…Proposed cfsw-SVM algorithms are then developed. Proposed formulations on SVM regularization parameter provides synergistic adjustments between prediction or classification accuracy and the level of correlations among features in the SVM implemented. …”
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  6. 6
    A web-based implementation of k-means algorithms

    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. …”
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  7. 7
    Implementation of Space Vector Modulation for Voltage Source Inverter

    Implementation of Space Vector Modulation for Voltage Source Inverter by Sanusi, Syamim, Ibrahim, Zulkifli, Jidin , Auzani, JOPRI, MOHD HATTA, Abdul Karim, Kasrul, Othman, Md Nazri

    Published 2013
    “…This paper presents a development of a voltage source inverter (VSI) for electrical drive applications based on Space Vector Modulation (SVM) technique and the SVM algorithm is implemented using digital signal processor (DSP). …”
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  8. 8
    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters

    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

    Published 2024
    “…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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  9. 9
    SVM based hysteresis current controller for a three phase active power filter

    SVM based hysteresis current controller for a three phase active power filter by Leow, Pei Ling, Ahmad Azli, Naziha

    Published 2004
    “…The switching control algorithms of the proposed SVM based HCC manage to generate compensated current according to the reference current harmonics extraction is based on the instantaneous active and reactive power theorem in time domain by calculating the power compensation. …”
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  10. 10
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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  11. 11
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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  12. 12
    SVM based hysteresis current controller for a three phase active power filter

    SVM based hysteresis current controller for a three phase active power filter by Leow, Pei Ling

    Published 2004
    “…The proposed SVM based HCC is implemented in a closed loop control system. …”
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  13. 13
    Image clustering comparison of two color segmentation techniques

    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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  14. 14
    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 last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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  15. 15
    Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman

    Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

    Published 2024
    “…In response to the unprecedented challenges posed by the COVID-19 pandemic, this research project presents a systematic approach to outbreak prediction, specifically advocating for the implementation of Support Vector Machine (SVM) algorithms. …”
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  16. 16
    Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm

    Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm by Yusof, Norzihani, Rosidi, Siti Aishah Rosidi, Ibrahim, Nuzulha Khilwani Ibrahim, Ahmed Ali, Ahmed El-Mogtaba Bannga

    Published 2020
    “…From the results, the different value of accuracy for both SVM and Naïve Bayes Algorithm was 2.4%. The Naïve Bayes Algorithm displayed better result comparing to SVM. …”
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  17. 17
    Lightning fault classification for transmission line using support vector machine

    Lightning fault classification for transmission line using support vector machine by Asman, Saidatul Habsah, Ab Aziz, Nur Fadilah, Ab Kadir, Mohd Zainal Abidin, Ungku Amirulddin, Ungku Anisa, Roslan, Nurzanariah, Elsanabary, Ahmed

    Published 2023
    “…The classification performance of the developed algorithms was evaluated using confusion matrix. Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN’s 70.60%. …”
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  18. 18
    Implementation of welch pre-processing in SVM algorithm for improved accuracy on EEG data

    Implementation of welch pre-processing in SVM algorithm for improved accuracy on EEG data by Hariyady Hariyady, Ag Asri Ag Ibrahim, Jason Teo, Muhammad Balya Firjaun Barlaman, Muhammad Aulanas Bitaqwa, Azhana Ahmad, Fouziah Md Yassin, Carolyn Salimun, Ng, Giap Weng

    Published 2024
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  19. 19
    A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island

    A comparison of support vector machine and decision tree classifications using satellite data of Langkawi Island by Mohd Shafri, Helmi Zulhaidi, Ramle, F. S. H.

    Published 2009
    “…The study indicates that the classification accuracy of SVM algorithm was better than DT algorithm. The overall accuracy of the SVM using four kernel types was above 73% and the overall accuracy of the DT method was 69%. …”
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  20. 20
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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