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  1. 1
    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…A novel feature extraction algorithm was developed to extract the feature vectors. …”
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  2. 2
    A framework of modified adaptive neuro-fuzzy inference engine

    A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

    Published 2012
    “…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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  3. 3
    Terahertz sensing analysis for early detection of ganoderma boninense disease using near infrared (NIR) spectrometer

    Terahertz sensing analysis for early detection of ganoderma boninense disease using near infrared (NIR) spectrometer by Mas Ira Syafila, Mohd Hilmi Tan

    Published 2023
    “…In classification, four different ML algorithms: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested to classify healthy and infected oil palm samples. …”
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  4. 4
    Stress mental health symptom assessment mobile application for young adults

    Stress mental health symptom assessment mobile application for young adults by Lee, Chun Hoong

    Published 2023
    “…As for the panic attack prediction feature, the application will transmit user-input responses to a model previously trained using historical data. Before this stage, the KNN algorithm is employed to construct the model using Google Form response data as part of the application development process. …”
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  5. 5
    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data

    Intelligent Fuzzy Classifier for Pre-Seizure Detection from Real Epileptic Data by Shakir, Mohamed, Malik, Aamir Saeed, Kamel, Nidal S., Qidwai, Uvais

    Published 2014
    “…In this paper, a classification method is presented using an Fuzzy Inference Engine to detect the incidences of preseizures in real/raw Epilepsy data. …”
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  6. 6
    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data

    Intelligent Fuzzy Classifier for pre-seizure detection from real epileptic data by Shakir, M., Malik, A.S., Kamel, N., Qidwai, U.

    Published 2014
    “…In this paper, a classification method is presented using an Fuzzy Inference Engine to detect the incidences of pre-seizures in real/raw Epilepsy data. …”
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  7. 7
    Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin

    Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin by Shamsuddin, Mohd Razif

    Published 2024
    “…Most of those research results varies as it uses different data, different network design, different parameters and optimizing algorithm. …”
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  8. 8
    From Employees to Entrepreneurs: A Qualitative Exploration of Career Transitions in Ghana

    From Employees to Entrepreneurs: A Qualitative Exploration of Career Transitions in Ghana by Gerhana, Yana Aditia

    Published 2025
    “…Based on the evaluation results using the confusion matrix, the Recall value was 59.1%, Precision was 100%, F1-Score was 74%, and Mean Absolute Error (MAE) of 0.97 (testing 31 data with 5 categories and target range 0-4), indicating that the recommendation system in the KMS has good classification capabilities and high accuracy in prediction. …”
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  9. 9
    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
    “…Based on the evaluation results using the confusion matrix, the Recall value was 59.1%, Precision was 100%, F1-Score was 74%, and Mean Absolute Error (MAE) of 0.97 (testing 31 data with 5 categories and target range 0-4), indicating that the recommendation system in the KMS has good classification capabilities and high accuracy in prediction. …”
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  10. 10
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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  11. 11
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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  12. 12
    Dengue classification system using clonal selection algorithm / Karimah Mohd

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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  13. 13
    Enhancing Classification Algorithms with Metaheuristic Technique

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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  14. 14
    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd

    Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

    Published 2022
    “…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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  15. 15
    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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  16. 16
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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  17. 17
    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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  18. 18
    Development of classification algorithms of human gait

    Development of classification algorithms of human gait by Koh, Chee Hong

    Published 2022
    “…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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  19. 19
    Text Extraction Algorithm for Web Text Classification

    Text Extraction Algorithm for Web Text Classification by Theab, Mustafa Muwafak

    Published 2010
    “…In this study, the experiment was conducted on five English educational websites. The created data sets are then classified using Naive-Bayes and C4.5 algorithms provided in WEKA application. …”
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  20. 20
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…According to the experimental findings, the suggested EB has a major effect on the accuracy, recall, and F-measure of data classification. The classification performance using EB outperforms other existing approaches for all datasets.…”
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