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  1. 1

    Airline flight delay prediction using Naïve Bayes algorithm / Ahmad Adib Baihaqi Shukri by Shukri, Ahmad Adib Baihaqi

    Published 2024
    “…This study aims to study the Naïve Bayes algorithm for flight delay prediction. The objective is to develop a reliable flight delay prediction model using the Naïve Bayes algorithm and evaluate its performance. …”
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    Thesis
  2. 2

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

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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    Thesis
  3. 3

    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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    Conference or Workshop Item
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    Evaluation of fall detection classification approaches by Kerdegari, Hamideh, Samsudin, Khairulmizam, Ramli, Abdul Rahman, Ghotoorlar, Saeid Mokaram

    Published 2012
    “…The acceleration data with a total data of 6962 instances and 29 attributes were used to evaluate the performance of the different classification algorithm. …”
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    Conference or Workshop Item
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    Classification and visualization on eligibility rate of applicant’s LinkedIn account using Naïve Bayes / Nurul Atirah Ahmad by Ahmad, Nurul Atirah

    Published 2023
    “…This project implements the Naive Bayes algorithm as the classification algorithm. …”
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    Thesis
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    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…Studies have shown how user perception can have a strong influence on policies and decision-making processes in a place, society, and nation. 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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    Analysis and comparison of classification algorithms for credit approval in Islamic banks by Pebrianti, Dwi, Wijanarko, Whena, Bayuaji, Luhur, Toha, Siti Fauziah

    Published 2025
    “…Although Islamic banks do not charge interest, profits are obtained through contracts, requiring thorough and accurate credit analysis. This study evaluates the performance of various classification algorithms, including C4.5, Random Forest, Decision Tree, K-Nearest Neighbors, and Naïve Bayes, in predicting credit approval decisions based on factors such as character, capacity, capital, collateral, and economic conditions. …”
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    Article
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    Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

    Published 2019
    “…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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    Thesis
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    An enhanced feature selection technique for classification of group based holy Quran verses by Abdullahi Oyekunle, Adeleke

    Published 2018
    “…The proposed FS technique is a combination of filter-based information gain (IG) and wrapper-based CFS algorithms. …”
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    Thesis
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    An enhanced feature selection technique for classification of group-based holy quran verses by Oyekunle, Adeleke Abdullahi

    Published 2018
    “…The proposed FS technique is a combination of JUter-based information gain (JG) and wrapper-based CFS algorithms. …”
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    Thesis
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    Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

    Published 2019
    “…The extracted features are then fed into the machine learning algorithm for classification process. Four popular machine learning algorithms include k-nearest neighbor (KNN), linear discriminate analysis (LDA), Naïve Bayes (NB) and support vector machine (SVM) are used in evaluation. …”
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    Article
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    An Automated System For Classifying Conference Papers by Ngan, Seon Choon Han

    Published 2021
    “…A randomised stratified 5- fold cross validation was then applied on several data mining algorithms and evaluated using the F-measure as a metric. …”
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    Final Year Project / Dissertation / Thesis
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    The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN by Rashid, Mamunur, Bari, Bifta Sama, Hasan, Md Jahid, Mohd Azraai, Mohd Razman, Rabiu Muazu, Musa, Ahmad Fakhri, Ab. Nasir, Anwar, P. P. Abdul Majeed

    Published 2021
    “…In the present investigation, an ensemble learning-based classification algorithm, namely random subspace k-nearest neighbour (k-NN) has been proposed to classify the motor imagery (MI) data. …”
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    Article
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    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

    Published 2025
    “…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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    Thesis
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    Using convolution neural networks for improving customer requirements classification performance of autonomous vehicle by Hao, Wang, Asrul, Adam, Fengrong, Han

    “…Most of conventional algorithms, such as, Naive Bayes, MAXENT, and support vector machine (SVM), only use limited human engineered features and their accuracy for customized corpus in sentences classification are proven low which is less than 50 percent. …”
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    Article
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