Search Results - data distribution ((bayes algorithm) OR (_ algorithm))

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  1. 1

    Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour by Pebrianti, Dwi, Ariawan, Angga, Bayuaji, Luhur, Mahdiana, Deni, ,, Rusdah

    Published 2022
    “…The validation of the proposed method is conducted by using a confusion matrix with a composition of 80% training data and 20% test data. The single Classifier test with the Naïve Bayes algorithm produces the highest accuracy value of 72.7%, while using k-NN algorithm is 81.5%. …”
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    Proceeding Paper
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    Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

    Published 2018
    “…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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    Article
  3. 3

    Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules by Wiliani, Ninuk

    Published 2023
    “…This research uses the Gaussian Naïve Bayes Algorithm using a ratio of training data and testing data of 70:30 resulting in an accuracy value of 46%. …”
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    Thesis
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    Spatial analysis of infant mortality in Peninsular Malaysia over three decades using mixture models by Nuzlinda Abdul Rahman, Abdul Aziz Jemain

    Published 2013
    “…Every component is assumed to have the same distribution, but different parameters. The number of optimum components were obtained by maximum likelihood approach via the EM algorithm. …”
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    Article
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    A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

    Published 2023
    “…However, accuracy of blind steganalysis algorithms highly depend on the features selected from the input data especially when attacking embedding techniques in TBS. …”
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    Thesis
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    Predicting the popularity of tweets using the theory of point processes. by Tan, Wai Hong

    Published 2019
    “…We further propose an inhomogeneous Poisson process model and an estimation method which utilizes internal and external knowledge, based on the times of historical retweets up to the censoring time, and the complete retweet sequences in the training data set respectively. The knowledge is combined using a novel empirical Bayes type approach, where the prior distribution for the model parameter is constructed based on the external knowledge, and the likelihood is calculated based on the internal knowledge. …”
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    UMK Etheses
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    Parameter estimation of Kumaraswamy Burr type X models based on cure models with or without covariates by Yusuf, Madaki Umar

    Published 2017
    “…In this thesis, we considered two methods via the classical maximum likelihood estimation (MLE) and the Bayes estimation using the Gibbs sampling (G-S) algorithm to estimate the parameters of BKBX, KBX and Beta-Weibull (BWB) models. …”
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    Thesis
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    A new hybrid ensemble feature selection framework for machine learning-based phishing detection system by Chiew, Kang Leng, Tan, Choon Lin, Wong, KokSheik, Yong, Kelvin S.C., Tiong, Wei King

    Published 2019
    “…In the first phase of HEFS, a novel Cumulative Distribution Function gradient (CDF-g) algorithm is exploited to produce primary feature subsets, which are then fed into a data perturbation ensemble to yield secondary feature subsets. …”
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    Article
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    Data discovery algorithm for scientific data grid environment by Abdullah, Azizol, Othman, Mohamed, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Othman, Abu Talib

    Published 2005
    “…By using this model, we study various discovery algorithms for locating data sets in a data grid system. …”
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    Article
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    Binary Vote Assignment on Cloud Quorum Algorithm for Fragmented MyGRANTS Database Replication by Noraziah, Ahmad, Ainul Azila, Che Fauzi, Herawan, Tutut, Zailani, Abdullah

    Published 2015
    “…We address how to build reliable systems by using the proposed BVACQ algorithm for distributed database fragmentation by using Malaysian Greater Research Network (MyGRANTS) data in our case study. …”
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    Article
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    Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J., Hasan, M.H.

    Published 2018
    “…It still takes a long time to compute the topic distribution of the data. There are still room for improvement in the time taken for the algorithm to complete the topic distribution. …”
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    Article
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    Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J., Hasan, M.H.

    Published 2018
    “…It still takes a long time to compute the topic distribution of the data. There are still room for improvement in the time taken for the algorithm to complete the topic distribution. …”
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    Article
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    Improved genetic algorithm for scheduling divisible data grid application by Kaid, Monir Abdullah Abduh, Othman, Mohamed, Ibrahim, Hamidah, K. Subramaniam, Shamala

    Published 2007
    “…Data Grid technology promises geographically distributed scientists to access and share physically distributed resources such as computing resources, networks, storages, and most importantly data collections for large scale data intensive problems. …”
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    Conference or Workshop Item
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    A novel binary vote assignment grid quorum algorithm for distributed database fragmentation by Ainul Azila, Che Fauzi, Noraziah, Ahmad, Noriyani, Mohd Zin

    Published 2011
    “…We address how to build reliable system by using the proposed BVAGQ algorithm for distributed database fragmentation. The result show that managing replication and transaction through proposed BVAGQ able to prepare data consistency.…”
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    Conference or Workshop Item
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    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

    Published 2018
    “…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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    Article