Search Results - (( developing emerging mining algorithm ) OR ( java implementation tree algorithm ))

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  1. 1

    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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    Article
  2. 2

    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 method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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    Thesis
  3. 3

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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    Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

    Published 2024
    “…Lately, a fully online buffer-based clustering algorithm for handling evolving data streams (BOCEDS) was developed. …”
    Article
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    A review on classifying and prioritizing user review-based software requirements by Salleh, Amran, Said, Mar Yah, Osman, Mohd Hafeez, Hassan, Sa’Adah

    Published 2024
    “…Investigating the potential of emerging machine learning models and algorithms to improve classification and prioritization accuracy is crucial. …”
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  13. 13

    An In-Depth Analysis of Text Clustering Techniques for Identifying Potential Insurance Customers on Social Media: A Machine Learning Perspective by Liew, Chun Kin, Goh, Ching Pang

    Published 2023
    “…This research focuses on the development of a social media web crawler, coupled with the implementation of sophisticated algorithms like Web Content Mining, Noisy Text Filtering, Named Entity Extraction, Part-Of-Speech (POS) Tagging, and Text Clustering. …”
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  14. 14

    Risk Concentration for Context Assessment (RiCCA) of SMS Messages using Danger Theory by Kamahazira Binti Zainal

    Published 2024
    “…This RiCCA prototype is developed from Danger Theory algorithms that is Dendritic Cell Algorithm (DCA) and Deterministic Dendritic Cell Algorithm (dDCA). …”
    thesis::doctoral thesis
  15. 15

    An In-Depth Analysis of Text Clustering Techniques for Identifying Potential Insurance Customers on Social Media: A Machine Learning Perspective by Liew, Chun Kin, Goh, Ching Pang

    Published 2023
    “…This research focuses on the development of a social media web crawler, coupled with the implementation of sophisticated algorithms like Web Content Mining, Noisy Text Filtering, Named Entity Extraction, Part-Of-Speech (POS) Tagging, and Text Clustering. …”
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  16. 16

    Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis by Kartiwi, Mira, Ab Rahman, Jamalludin, Nik Mohamed, Mohamad Haniki, Draman, Samsul, Ab Rahman, Norny Syafinaz

    Published 2017
    “…The predictive model was developed using Induction Decision Tree (ID3) algorithm, a popular data mining technique an exploratory tool for knowledge discovery. …”
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  17. 17

    Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

    Published 2019
    “…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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    Thesis
  18. 18

    Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

    Published 2025
    “…Four machine learning algorithms—Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Logistic Regression (LR)—were developed to predict ACL injury. …”
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