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  1. 1
    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
    “…This algorithm was compared to co-spectral plot method for labelling clusters the clusters generated in Landsat TM dataset. …”
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  2. 2
    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
    “…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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  3. 3
    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
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  4. 4
    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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  5. 5
    Multi-label learning based on positive label correlations using predictive apriori

    Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

    Published 2019
    “…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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  6. 6
    Multi label ranking based on positive pairwise correlations among labels

    Multi label ranking based on positive pairwise correlations among labels by Alazaidah, Raed, Ahmad, Farzana Kabir, Mohsin, Mohamad

    Published 2020
    “…Multi-Label Classification (MLC) is a general type of classification that has attracted many researchers in the last few years. …”
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  7. 7
    Application of Optimization Methods for Solving Clustering and Classification Problems

    Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

    Published 2011
    “…The focus of this thesis is on solvingclustering and classification problems. Specifically, we will focus on new optimization methods for solving clustering and classification problems. …”
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  8. 8
    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

    Published 2018
    “…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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  9. 9
    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
    “…For this reason, in this research,several auxiliary algorithms are introduced to improve the performance of the classification algorithm, namely the meta-heuristic algorithm. …”
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  10. 10
    The classification of FTIR plastic bag spectra via label spreading and stacking

    The classification of FTIR plastic bag spectra via label spreading and stacking by Almanifi, Omair Rashed Abdulwareth, Ng, Jee Kwan, Anwar P. P., Abdul Majeed

    Published 2021
    “…Four pipelines were investigated, consisting of two machine learning algorithms, a stacked model that stacks the KNN, SVM and RF algorithms together, and Label spreading, as well as two different dimensionality reduction methods namely; SVD and UMAP. …”
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  11. 11
    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan C.H., Tan M.S., Chang S.-W., Yap K.S., Yap H.J., Wong S.Y.

    Published 2023
    “…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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  12. 12
    Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout

    Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

    Published 2025
    “…The study employed two MLC frameworks: Problem Transformation methods (Binary Relevance, Classifier Chains, Label Power Set, and Calibrated Label Ranking) and Algorithm Adaptation. …”
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  13. 13
    Knowledge base processing method based on text classification algorithm

    Knowledge base processing method based on text classification algorithm by Baisheng Zhong, Mohd Shamrie Sainin, Tan Soo Fun

    Published 2023
    “…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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  14. 14
    Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm

    Real-time classification improvement of Indonesian sign system letters (SIBI) using K-Nearest Neighbor algorithm by Dhewa, Oktaf Agni, Utama, Safitri Yuliana, Nasuha, Aris, Gunawan, Teddy Surya, Pratama, Gilang Nugraha Putu

    Published 2024
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  15. 15
    An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks

    An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks by Ihsanto, Eko, Ramli, Kalamullah, Sudiana, Dodi, Gunawan, Teddy Surya

    Published 2020
    “…Many algorithms have been developed for automated electrocardiogram (ECG) classification. …”
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  16. 16
    Chain coding and pre processing stages of handwritten character image file

    Chain coding and pre processing stages of handwritten character image file by Suliman, Azizah, Sulaiman, Md. Nasir, Othman, Mohamed, O. K. Rahmat, Rahmita Wirza

    Published 2010
    “…Fuzzy Logic is used in the classification phase while HMM is used in the process of extracting features for the preparation of linguistic variables of the fuzzy rules. …”
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  17. 17
    Improved method of classification algorithms for crime prediction

    Improved method of classification algorithms for crime prediction by Babakura, Abba, Sulaiman, Md. Nasir, Yusuf, Mahmud Ahmad

    Published 2014
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  18. 18
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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  19. 19
    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD

    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

    Published 2012
    “…Unique features from the I", 4t h ,7th and 8thl evel details are obtained as criteria for developing a Rules-Based Algorithm for classifying disturbances that have occurred. …”
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  20. 20
    AN INTEGRATED GENERIC TEXT CLASSIFICATION ALGORITHM FOR INDONESIAN AND MALAY NEWS DOCUMENTS

    AN INTEGRATED GENERIC TEXT CLASSIFICATION ALGORITHM FOR INDONESIAN AND MALAY NEWS DOCUMENTS by ,, ZUL INDRA

    Published 2016
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