Search Results - (( evolution optimization methods algorithm ) OR ( features selection mining algorithm ))

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  1. 1

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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    Thesis
  2. 2

    Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

    Published 2019
    “…It is very necessary to increase the quality of dataset as to get better prediction results. There are many feature selection algorithms, however three filter feature selection algorithms FCBF, Chi-Square, and ReliefF are selected due their better performance, and applied on three different studentâ��s data sets. …”
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    Article
  3. 3

    Comparing the performance of FCBF, Chi-Square and relief-F filter feature selection algorithms in educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

    Published 2019
    “…It is very necessary to increase the quality of dataset as to get better prediction results. There are many feature selection algorithms, however three filter feature selection algorithms FCBF, Chi-Square, and ReliefF are selected due their better performance, and applied on three different studentâ��s data sets. …”
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    Article
  4. 4

    Evaluation of data mining models for predicting concrete strength by Wong, Chuan Ming

    Published 2024
    “…These models are all evaluated with hyperparameter tuning and different feature selection techniques. The feature selection techniques included are (i) Principle Component Analysis, (ii) Boruta and (iii) LASSO. …”
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    Final Year Project / Dissertation / Thesis
  5. 5

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
    “…In this thesis, a novel weighted feature selection approach on nominal features is proposed, for a partition. clustering algorithm that can handle mixed data. …”
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    Thesis
  6. 6

    Performance analysis of feature selection algorithm for educational data mining by Zaffar, M., Hashmani, M.A., Savita, K.S.

    Published 2018
    “…This paper present an analysis of the performance of feature selection algorithms on student data set. …”
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    Article
  7. 7

    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
  8. 8

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In comparison to different single algorithms for feature selection,experimental results show that the proposed ensemble method is able to reduce dimensionality, the number of irrelevant features and produce reasonable classifier accuracy. …”
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    Thesis
  9. 9

    Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms by Anuar N.K., Bakar A.A., Ahmad A.R., Yussof S., Rahim F.A., Ramli R., Ismail R.

    Published 2023
    “…Data Analytics; Data mining; Decision making; Feature extraction; Machine learning; Predictive analytics; Privacy by design; Features selection; Fine grains; No leakages; Predictive modeling; Privacy preserving; Learning algorithms…”
    Conference Paper
  10. 10

    Feature selection with integrated Gaussian seahorse optimization data mining for cross-border business cooperation between the Malaysian medical industry and tourism industry by Ma, Yuaner, Jabar, Juhaini, Abdul Aziz, Nor Azah

    Published 2023
    “…The integrated GSH-DM approach showcases the potential of combining feature selection techniques with advanced optimization algorithms in data mining applications. …”
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    Article
  11. 11

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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    Thesis
  12. 12

    Identifying significant features and data mining techniques in predicting cardiovascular disease / Mohammad Shafenoor Amin by Mohammad Shafenoor , Amin

    Published 2018
    “…A thorough analysis of the features needs to be conducted to select a combination of significant features that can increase the accuracy of the prediction. …”
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    Thesis
  13. 13

    Analysis of Feature Selection Methods for Sentiment Analysis Concerning Covid-19 Vaccination Issues by Muhammad, Fajar, Tri Basuki, Kurniawan, Edi Surya, Negara Harahap

    Published 2023
    “…For this reason, the feature selection method will be used in this study to select features or terms that contribute more to decisions or labels. …”
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    Article
  14. 14

    Feature Selection with Harmony Search for Classification: A Review by Norfadzlan, Yusup, Azlan, Mohd Zain, Nur Fatin Liyana, Mohd Rosely, Suhaila Mohamad, Yusuf

    Published 2021
    “…In the area of data mining, feature selection is an important task for classification and dimensionality reduction. …”
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    Proceeding
  15. 15

    Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

    Published 2019
    “…Attribute selection which is also known as feature selection is an essential process that is relevant to predictive analysis.To date, various feature selection algorithms have been introduced, nevertheless they all work independently. …”
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    Article
  16. 16

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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    Thesis
  17. 17

    An ensemble feature selection method to detect web spam by Oskouei, Mahdieh Danandeh, Razavi, Seyed Naser

    Published 2018
    “…Feature selection is an important issue in data mining, and it is used to reduce dimensions of features set. …”
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    Article
  18. 18

    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

    Published 2024
    “…The newly proposed logical rule and the algorithm will be the components in the logic mining model namely Weighted Systematic 2 Satisfiability Modified Reverse Analysis. …”
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    Thesis
  19. 19

    Feature Selection And Enhanced Krill Herd Algorithm For Text Document Clustering by Abualigah, Laith Mohammad Qasim

    Published 2018
    “…In this study, a new method for solving the TD clustering problem worked in the following two stages: (i) A new feature selection method using particle swarm optimization algorithm with a novel weighting scheme and a detailed dimension reduction technique are proposed to obtain a new subset of more informative features with low-dimensional space.…”
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    Thesis
  20. 20

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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    Article