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  1. 1
    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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  2. 2
    Investigating optimal smartphone placement for identifying stairs movement using machine learning

    Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

    Published 2023
    “…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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  3. 3
    Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms

    Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms by Anuar N.K., Bakar A.A., Ahmad A.R., Yussof S., Rahim F.A., Ramli R., Ismail R.

    Published 2023
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  4. 4
    Identification model for hearing loss symptoms using machine learning techniques

    Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

    Published 2014
    “…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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  5. 5
    Personal identification by Keystroke Pattern for login security

    Personal identification by Keystroke Pattern for login security by Abdullah, Norhayati

    Published 2001
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  6. 6
    Analysis of banana plant health using machine learning techniques

    Analysis of banana plant health using machine learning techniques by Thiagarajan, Joshva Devadas, Kulkarni, Siddharaj Vitthal, Jadhav, Shreyas Anil, Waghe, Ayush Ashish, Raja, S.P., Rajagopal, Sivakumar, Poddar, Harshit, Subramaniam, Shamala

    Published 2024
    “…Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. …”
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  7. 7
    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 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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  8. 8
    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
    “…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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  9. 9
    Early Detection Of ADHD Among Children Using Machine Learning

    Early Detection Of ADHD Among Children Using Machine Learning by Nur Atiqah, Kamal

    Published 2023
    “…Machine learning algorithms can analyze fMRI data and identify biomarkers indicative of ADHD, enabling accurate classification. …”
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  10. 10
    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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  11. 11
    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida

    Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida by Nanyonga , Aziida

    Published 2019
    “…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. …”
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  12. 12
    Adaptive Non-Stationary Cardiac Signals Identification using an Augmented MLP Network

    Adaptive Non-Stationary Cardiac Signals Identification using an Augmented MLP Network by Asirvadam , Vijanth Sagayan, McLoone, Sean

    Published 2007
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  13. 13
    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN

    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

    Published 2011
    “…For the third contribution, we have applied the Self-Training algorithm which is one of the semi-supervised machines learning technique. …”
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  14. 14
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    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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  15. 15
    Advancing machine learning for identifying cardiovascular disease via granular computing

    Advancing machine learning for identifying cardiovascular disease via granular computing by Ku Muhammad Naim, Ku Khalif, Noryanti, Muhammad, Mohd Khairul Bazli, Mohd Aziz, Mohammad Isa, Irawan, Mohammad Iqbal, ., Muhammad Nanda, Setiawan

    Published 2024
    “…Early-stage cardiovascular illness can benefit from machine learning models in drug selection. The integration of granular computing, specifically z-numbers, with machine learning algorithms, is suggested for CVD identification. …”
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  16. 16
    Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki

    Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki by Mohd Zaki, Sofea Najihah

    Published 2024
    “…Further enhancements might involve including machine learning algorithms to improve the prototype's accuracy by learning from a larger dataset, which would eventually improve the prototype's ability to offer deep understanding into handwriting patterns related to dyslexia.…”
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  17. 17
    DNA enhancer prediction using machine learning techniques with novel feature representation

    DNA enhancer prediction using machine learning techniques with novel feature representation by Fong, Pui Kwan

    Published 2016
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  18. 18
    Deep plant: A deep learning approach for plant classification / Lee Sue Han

    Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

    Published 2018
    “…The existing CNN based approaches can only capture the similar region-wise patterns within an image but not the structural patterns of a plant composed of varying number of plant views images composed of one or more organs. …”
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  19. 19
    Feature selection for Malaysian medicinal plant leaf shape identification and classification

    Feature selection for Malaysian medicinal plant leaf shape identification and classification by Sainin, Mohd Shamrie, Alfred, Rayner

    Published 2014
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  20. 20
    Preserving the topology of self-organizing maps for data analysis: A review

    Preserving the topology of self-organizing maps for data analysis: A review by Bariah, Yusob, Zuriani, Mustaffa, Siti Mariyam, Shamsuddin

    Published 2020
    “…This paper presents detail explanation on SOM learning algorithm and its applications. Some issues related to SOM's architecture are also discussed, namely the formulation of training data from input samples, and the Best Matching Unit (BMU) identification for better visualization of large datasets, and improvement made to the SOM algorithm.…”
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