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  1. 1
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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  2. 2
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…Some of the features may contain irrelevant information caused by data redundancy or by noise. A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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  3. 3
    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
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  4. 4
    3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm

    3D LiDAR Vehicle Perception and Classification Using 3D Machine Learning Algorithm by Yong, Ericsson, Muhammad Aizzat, Zakaria, Mohamad Heerwan, Peeie, M. Izhar, Ishak

    Published 2024
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  5. 5
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  6. 6
    Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali

    Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali by Mohd Razali, Farah Nabila

    Published 2025
    “…The Naive Bayes algorithm was chosen for its efficiency in text classification and ability to handle large volumes of unstructured data. …”
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  7. 7
    Development of seven segment display recognition using TensorFlow on Raspberry Pi

    Development of seven segment display recognition using TensorFlow on Raspberry Pi by Gunawan, Teddy Surya, Mohammad Reduwan, Haque, Yaacob, Mashkuri, Mohamed Azmin, Nor Fadhillah, Ismail, Nanang, Ismail, Md Yusof, Kartiwi, Mira, A. Rahman, Azhar

    Published 2022
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  8. 8
    A literature review on text classification and sentiment analysis approaches

    A literature review on text classification and sentiment analysis approaches by Wang Dawei, Rayner Alfred, Joe Henry Obit, Chin Kim On

    Published 2021
    “…In the system architecture, same as text classification, the complete classification systemmainly contains data acquisition, data pre-process, feature extraction, classification algorithm and result output.TheWeb crawler usually be used in first step, the URL Link, hashtags, Non-Chinese text should be removed in second step. …”
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  9. 9
    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
    “…This study attempts to predict the success rate of students’ academic performance by analyzing their examination results to secure a place at college level for the subsequent semester. 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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  10. 10
    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
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  11. 11
    Automated classification of celestial objects using machine learning

    Automated classification of celestial objects using machine learning by Muhamad Suwaid, Muhammad Aiman Haris, Ab Karim, Muhammad ‘Ilyas Amierrullah, Hassan, Raini, Abdul Aziz, Azni

    Published 2025
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  12. 12
    Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis

    Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis by Nor Farawahida Abdullah, Nur Haizum Abd Rahman

    Published 2025
    “…The machine learning algorithm, support vector machine (SVM), is then created to automatically identify and classify comments about EV acceptance and perception. …”
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  13. 13
    Classification of Parkinson's Disease (PD) Based on Multilayer Perception (MLPs) Neural Network and Anova as a feature extraction / Zahari Abu Bakar ... [et al.]

    Classification of Parkinson's Disease (PD) Based on Multilayer Perception (MLPs) Neural Network and Anova as a feature extraction / Zahari Abu Bakar ... [et al.] by Abu Bakar, Zahari, Ibrahim, Nur Farahiah, Ispawi, Dzufi Iszura, Md. Tahir, Nooritawati

    Published 2012
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  14. 14
    Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis

    Consumer acceptance and perceptions of electric vehicles in Malaysia using sentiment analysis by Nor Farawahida, Abdullah, Nur Haizum, Abd Rahman

    Published 2025
    “…The machine learning algorithm, support vector machine (SVM), is then created to automatically identify and classify comments about EV acceptance and perception. …”
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  15. 15
    Uncovering user perceptions toward digital banks in Indonesia: A Naïve Bayes sentiment analysis of twitter data

    Uncovering user perceptions toward digital banks in Indonesia: A Naïve Bayes sentiment analysis of twitter data by Karmagatri, Mulyani, Aziz, Clarisa Fezia Amanda, Asih, Wini Rizki Purnama, Jumbri, Isma Addi

    Published 2023
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  16. 16
    Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis

    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
    Predicting Customer Behaviour on Buying Life Insurance using Machine Learning

    Predicting Customer Behaviour on Buying Life Insurance using Machine Learning by Fabu Ayub A Ghafar, Norhana Abd Rahim, Yumn Suhaylah Yusoff

    Published 2026
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  18. 18
    Handgrip strength evaluation using neuro fuzzy approach

    Handgrip strength evaluation using neuro fuzzy approach by Seng, W.C., Chitsaz, M.

    Published 2010
    “…The fuzzy model based on the membership function, fed in by the neural network will intelligently classify the data. The results indicate that the classification accuracy of normal and pathological patients are 90 and 75 respectively. …”
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  19. 19
    Simple quantum circuit for pattern recognition based on nearest mean classifier

    Simple quantum circuit for pattern recognition based on nearest mean classifier by Mahmoud Ahmed, Gharib Subhi, Messikh Azeddine, Azeddine

    Published 2016
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  20. 20
    Sentiment analysis regarding childcare issues using Naive Bayes Algorithm / Alis Farhana Zulkipeli

    Sentiment analysis regarding childcare issues using Naive Bayes Algorithm / Alis Farhana Zulkipeli by Zulkipeli, Alis Farhana

    Published 2025
    “…This study applies the Naive Bayes algorithm for sentiment analysis to assess public perceptions of childcare issues, particularly child abandonment and accidents. …”
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