Search Results - (( java application mining algorithm ) OR ( learning implementation level 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
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    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
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    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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  6. 6
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  7. 7
    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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  8. 8
    IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH

    IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH by MOHD YAKOP, SITI HAJAR

    Published 2006
    “…The objective of this project is to develop algorithms inMATLAB and be able to implement image texture analysis by using the developed algorithms. …”
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  9. 9
    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
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  10. 10
    Autism Spectrum Disorder Classification Using Deep Learning

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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  11. 11
    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview

    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

    Published 2019
    “…Deep learning provides the mechanism to RL which enables the agent to solve the human level task. …”
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  12. 12
    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview

    Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

    Published 2019
    “…Deep learning provides the mechanism to RL which enables the agent to solve the human level task. …”
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  13. 13
    EEG-based emotion recognition using machine learning algorithms

    EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

    Published 2024
    “…Thus, this project proposed an optimised machine learning algorithms to classify emotion by analysing brain activity using Electroencephalogram (EEG) signals. …”
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  14. 14
    Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.]

    Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.] by Abd Rahman, Abdullah Sani, Meutia, Rita, Hamid, Yusnaliza, Abdul Rahman, Rahayu

    Published 2022
    “…In supporting the intervention approaches, machine learning techniques have been widely utilized. Another challenge is the difficulty to implement machine learning analysis by the educators. …”
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  15. 15
    Jogging activity recognition using k-NN algorithm

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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    Academic Exercise
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  16. 16
    Prediction of the level of air pollution during wildfires using machine learning classification methods

    Prediction of the level of air pollution during wildfires using machine learning classification methods by Khalid, Syed Mohammed, Hassan, Raini

    Published 2020
    “…Recent studies indicate that data retrieved from remote sensing satellites is now an emerging alternative for air quality prediction at the ground level. Hence, this research aims to use satellite-based data to predict the air quality of East Malaysian cities with the help of different Machine Learning classification algorithms. …”
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  17. 17
    An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions

    An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions by Gerhana, Yana Aditia

    Published 2025
    “…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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  18. 18
    Estimating Depressive Tendencies Of Twitter User Via Social Media Data

    Estimating Depressive Tendencies Of Twitter User Via Social Media Data by Loh, Hooi Teng

    Published 2023
    “…The twitter dataset can be used to test the level of depressive tendencies with three different machine learning algorithms. …”
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    Undergraduates Project Papers
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  19. 19
    Web Usage Mining for UUM Learning Care Using Association Rules

    Web Usage Mining for UUM Learning Care Using Association Rules by Azizul Azhar, Ramli

    Published 2004
    “…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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  20. 20
    Assessing the outcome of Competencies Level from Knowledge-Based Project

    Assessing the outcome of Competencies Level from Knowledge-Based Project by Sungsinlert, Anyamanee

    Published 2008
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