Search Results - (( java implementation mining algorithm ) OR ( using bayesian tree algorithm ))

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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
    Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms

    Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

    Published 2024
    “…Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. …”
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  4. 4
    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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  5. 5
    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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  6. 6
    An experimental study of classification algorithms for crime prediction.

    An experimental study of classification algorithms for crime prediction. by Iqbal, Rizwan, Azmi Murad, Masrah Azrifah, Mustapha, Aida, Panahy, Payam Hassany Shariat, Khanahmadliravi, Nasim

    Published 2013
    “…The results from the experiment showed that, Decision Tree algorithm out performed Naïve Bayesian algorithm and achieved 83.9519% Accuracy in predicting ‘Crime Category’ for different states of USA.…”
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  7. 7
    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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  8. 8
    Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study

    Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study by Abu-Samah A., Razak N.N.A., Suhaimi F.M., Jamaludin U.K., Chase J.G.

    Published 2023
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  9. 9
    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data

    Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

    Published 2018
    “…Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. …”
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  10. 10
    Linking Bayesian Network and Intensive Care Units Data: A Glycemic Control Study

    Linking Bayesian Network and Intensive Care Units Data: A Glycemic Control Study by Abu-Samah A., Abdul Razak N.N., Mohamad Suhaimi F., Jamaludin U.K., Chase G.

    Published 2023
    Conference Paper
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  11. 11
    E4ML: Educational Tool for Machine Learning

    E4ML: Educational Tool for Machine Learning by Sainin, Mohd Shamrie, Siraj, Fadzilah

    Published 2003
    “…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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  12. 12
    Text Summarization System with Bayesian Theorem on Oil & Gas Drilling Topic

    Text Summarization System with Bayesian Theorem on Oil & Gas Drilling Topic by Kurniawan, Iwan

    Published 2007
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    Final Year Project
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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
    A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works

    A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

    Published 2023
    Conference Paper
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  15. 15
    A study on classification learning algorithms to predict crime status.

    A study on classification learning algorithms to predict crime status. by Shojaee, Somayeh, Mustapha, Aida, Sidi, Fatimah, A. Jabar, Marzanah

    Published 2013
    “…In this paper, we conducted an experiment to obtain better supervised classification learning algorithms to predict crime status by using two different feature selection methods tested on real dataset. …”
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  16. 16
    Features selection for intrusion detection system using hybridize PSO-SVM

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

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  17. 17
    Prediction of college student academic performance using data mining techniques.

    Prediction of college student academic performance using data mining techniques. by Abd Jalil, Azura, Mustapha, Aida, Santa, Dzulizah, Zain, Nurul Zaiha, Radwan, Rizalina

    Published 2013
    “…The classification algorithms used are the Decision Tree, Naïve Bayesian, and Multilayer Perception with the highest classification accuracy by the Naive Bayes algorithm with accuracy of 95.3%. …”
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  18. 18
    Beyond Grades - Predicting Programme Learning Outcomes with Multi-Output Regression in Malaysian Higher Education

    Beyond Grades - Predicting Programme Learning Outcomes with Multi-Output Regression in Malaysian Higher Education by Muhammad Noorazizi Abd Ghani, Istas Fahrurrazi Nusyirwan

    Published 2025
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  19. 19
    A comparative analysis of predicting heart disease using machine learning algorithms

    A comparative analysis of predicting heart disease using machine learning algorithms by Nur Hidayah, Azmidi, Noryanti, Muhammad, Abubakar, Bala, Norhayati, Rosli, Najihah, Mohamed

    Published 2026
    “…This study applies six machine learning algorithms, including K-nearest neighbors, logistic regression, Bayesian classifier, decision tree, random forest, and support vector machine. …”
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  20. 20
    Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease

    Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

    Published 2024
    “…The LightGBM algorithm was selected for its efficiency in classification tasks, and Bayesian Optimization with Tree-structured Parzen Estimator (TPE) was employed to fine-tune its hyperparameters. …”
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