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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  2. 2
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset

    Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset by Amirruddin, A., Aziz, I.A., Hasan, M.H.

    Published 2020
    “…This problem inspires the idea to develop a prediction algorithm to predict the missing values in the dataset, where Support vector regression (SVR) has been proposed as a prediction method to predict missing values in several academic types of researches. …”
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  7. 7
    An Evaluation of Machine Learning Algorithms for Missing Values Imputation

    An Evaluation of Machine Learning Algorithms for Missing Values Imputation by Kohbalan, Moorthy, Ali, Mohammed Hasan, Mohd Arfian, Ismail, Chan, Weng Howe, Mohd Saberi, Mohamad, Safaai, Deris

    Published 2019
    “…It represents the research and imputation of missing values in gene expression data. By using the local or global correlation of the data we focus mostly on the contrast of the algorithms. …”
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  8. 8
    Missing-values imputation algorithms for microarray gene expression data

    Missing-values imputation algorithms for microarray gene expression data by Moorthy, Kohbalan, Jaber, Aws Naser, Mohd Arfian, Ismail, Ernawan, Ferda, Mohd Saberi, Mohamad, Safaai, Deris

    Published 2019
    “…Numerous bioinformatics examination tools are used for cancer prediction, including the data set matrix (Bailey et al., Cell 173(2):371–385, 2018); thus, it is necessary to resolve the problem of missing-values imputation. …”
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  9. 9
    Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method(NNM) and Expectation-Maximization (EM) Algorithm

    Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method(NNM) and Expectation-Maximization (EM) Algorithm by Muhammad Izzuddin Rumaling, Chee, Fuei Pien, Jedol Dayou, Chang, Jackson Hian Wui, Steven Soon Kai Kong, Justin Sentian

    Published 2020
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  10. 10
    An improved K-nearest neighbour with grasshopper optimization algorithm for imputation of missing data

    An improved K-nearest neighbour with grasshopper optimization algorithm for imputation of missing data by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani

    Published 2021
    “…K-nearest neighbors (KNN) has been extensively used as imputation algorithm to substitute missing data with plausible values. …”
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  11. 11
    Systematic review on missing data imputation techniques with machine learning algorithms for healthcare

    Systematic review on missing data imputation techniques with machine learning algorithms for healthcare by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Maen, Mohd Khaled

    Published 2022
    “…Many machine learning algorithms have been applied to impute missing data with plausible values. …”
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  12. 12
    Detection Of Misplaced And Missing Regions In Image Using Neural Network

    Detection Of Misplaced And Missing Regions In Image Using Neural Network by Tan , Jin Siang

    Published 2017
    “…The neural network uses the RGB value from the image processing phase and analyzes the regions to check whether there is misplaced or missing jigsaw puzzle. …”
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  13. 13
    Improving knowledge extraction of Hadith classifier using decision tree algorithm

    Improving knowledge extraction of Hadith classifier using decision tree algorithm by Aldhaln, Kawther, Zeki, Akram M., Zeki, Ahmed M., Alreshidi, Hamad

    Published 2012
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  14. 14
    DISSERTATION TITLE: AN OPTIMIZED SUPPORT VECTOR REGRESSION USING EVOLVED BAT ALGORITHM FOR HANDLING MISSING VALUES IN DATASETS

    DISSERTATION TITLE: AN OPTIMIZED SUPPORT VECTOR REGRESSION USING EVOLVED BAT ALGORITHM FOR HANDLING MISSING VALUES IN DATASETS

    Published 2022
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  15. 15
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Missing values lead to the difficulty of extracting useful information from that data set. …”
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  16. 16
    ExtraImpute: a novel machine learning method for missing data imputation

    ExtraImpute: a novel machine learning method for missing data imputation by Alabadla, Mustafa, Sidi, Fatimah, Ishak, Iskandar, Ibrahim, Hamidah, Affendey, Lilly Suriani, Hamdan, Hazlina

    Published 2022
    “…This approach imputes each missing value that exists in features by predicting its value using other observed values in the dataset. …”
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  17. 17
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  18. 18
    Enhanced mechanism to handle missing data of Hadith classifier

    Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

    Published 2011
    “…Decision tree algorithms have the ability to deal with missing values or wrong data. …”
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  19. 19
    Missing values imputation tool using imputex algorithm

    Missing values imputation tool using imputex algorithm by Sidi, Fatimah, Abdullah, Lili Nurliyana, Alabadla, Mustafa, Ishak, Iskandar

    Published 2024
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  20. 20
    Missing value estimation methods for data in linear functional relationship model

    Missing value estimation methods for data in linear functional relationship model by Adilah Abdul Ghapor, Yong Zulina Zubairi, A.H.M. Rahmatullah Imon

    Published 2017
    “…Missing value problem is common when analysing quantitative data. …”
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