Search Results - (( data distribution _ algorithm ) OR ( pre evaluation ((case algorithm) OR (bayes algorithm)) ))

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  1. 1

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

    Published 2004
    “…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. 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
  2. 2

    Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

    Published 2022
    “…The proposed algorithm was developed through the stages of: data pre-processing, feature identification and extraction with either t-Distributed Stochastic Neighbour Embedding (t-SNE) or principal component analysis (PCA)), clustering (K-means clustering, Hierarchical clustering, and Fuzzy C-means clustering) and characteristics interpretation with statistical analysis. …”
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    Article
  3. 3

    Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

    Published 2021
    “…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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    Thesis
  4. 4

    Multi-Objectives Memetic Discrete Differential Evolution Algorithm for Solving the Container Pre-Marshalling Problem by Mustafa, Hossam M. J., Ayob, Masri, Ahmad Nazri, Mohd Zakree, Abu-Taleb, Sawsan

    Published 2019
    “…In addition, it improves the exploration and exploitation capabilities of the algorithm. The standard pre-marshalling benchmark dataset (i.e., Bortfeldt-Forster) is used to evaluate the effectiveness of the proposed algorithm. …”
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    Article
  5. 5

    Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak by Rajogoval, Illayakantthan

    Published 2022
    “…Two case studies related to the COVID-19 outbreak in Malaysia and Malta were used. …”
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    Monograph
  6. 6

    Evaluation of data mining classification and clustering techniques for diabetes / Tuba Pala and Ali Yilmaz Camurcu by Pala, Tuba, Camurcu, Ali Yilmaz

    Published 2014
    “…The success evaluation of data mining classification algorithms have been realized through the data mining programs Weka and RapidMiner. …”
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    Article
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    Optimizing sentiment analysis of Indonesian texts: Enhancing deep learning models with genetic algorithm-based feature selection by Siti, Mujilahwati, Noor Zuraidin, Mohd Safar, Ku Muhammad Naim, Ku Khalif, Nasyitah, Ghazalli

    Published 2024
    “…This study examines the optimization of Indonesian text sentiment analysis through the integration of feature selection using a genetic algorithm (GA) with deep learning models. The application of GA for data dimensionality reduction from 41,140 to 20,769 features, coupled with fitness evaluation based on SVM, resulted in an observed increase in accuracy by 8.10% for SVM, 36.1% for Naïve Bayes, 7.82% for LSTM, 5.47% for DNN, and 6.25% for CNN. …”
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    Article
  9. 9
  10. 10

    Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

    Published 2024
    “…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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    Thesis
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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
  14. 14

    Fake news detection: A machine learning approach by Yeoh, Dennis Guan Lee

    Published 2021
    “…The final model chosen to be deployed was a model trained using a Multinomial Naïve Bayes algorithm.…”
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    Final Year Project / Dissertation / Thesis
  15. 15

    Block based low complexity iterative QR precoder structure for Massive MIMO by Mok, Li Suet

    Published 2021
    “…We also study one of the suboptimal pre-coding solutions known as Block-diagonalization (BD) applicable in the case where a receiver has multiple antennas and compare their performance. …”
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    Thesis
  16. 16

    Sentiment analysis on the place of interest in Malaysia by Qiryn Adriana, Khairul Zaman, Wan Nur Syahidah, Wan Yusoff, Qistina Batrisyia, Azman Shah

    Published 2025
    “…The dataset was then split into training and testing sets, and three supervised learning algorithms which are Support Vector Machine, Random Forest, and Naive Bayes were employed to evaluate the sentiment analysis models. …”
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    Article
  17. 17

    Predictive analytics for the sentiment of malaysian place of interest using machine learning models by Qiryn Adriana, Kharul Zaman

    Published 2023
    “…The data was then divided into training and testing sets, and was trained using three different supervised learning algorithms, namely Support Vector Machine, Random Forest, and Naive Bayes. …”
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    Undergraduates Project Papers
  18. 18

    A semantic conceptualization on tagged bag-of concepts to improve accuracy for sentiment Analysis by Mehanna, Yassin Samir Hassan

    Published 2023
    “…In addition, the most efficient lexicons and pre-processing techniques are investigated in improving the accuracy of SA. …”
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    Thesis
  19. 19

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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    Thesis
  20. 20

    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