Search Results - missing process analysis

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  1. 1
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani, Emran, Nurul Akmar

    Published 2018
    “…Missing values is a universal problem in many research domains that is commonly encountered in the data cleaning process. …”
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  2. 2
    Performance analysis of machine learning algorithms for missing value imputation

    Performance analysis of machine learning algorithms for missing value imputation by Ismail, Amelia Ritahani, Zainal Abidin, Nadzurah, Emran, Nurul Akmar

    Published 2018
    “…Data mining requires a pre-processing task in which the data are prepared,cleaned,integrated,transformed,reduced and discretized for ensuring the quality.Missing values is a universal problem in many research domains that is commonly encountered in the data cleaning process.Missing values usually occur when a value of stored data absent for a variable of an observation.Missing values problem imposes undesirable effect on analysis results,especially when it leads to biased parameter estimates.Data imputation is a common way to deal with missing values where the missing value’s substitutes are discovered through statistical or machine learning techniques. …”
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  3. 3
    Cold deck missing value imputation with a trust-based selection method of multiple web donors

    Cold deck missing value imputation with a trust-based selection method of multiple web donors by Mohd Jaya, Mohd Izham

    Published 2018
    “…Missing value is a common problem in any dataset and its occurrence decreases data completeness as data values are missing. …”
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  4. 4
    Crown counting and mapping of missing oil palm tree using airborne imaging system

    Crown counting and mapping of missing oil palm tree using airborne imaging system by Kee, Ya Wern

    Published 2019
    “…Therefore, this study implemented different image processing techniques to true color and multispectral UAV imageries for automated existing and missing oil palm tree counting. …”
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  5. 5
    Object detection and near-miss analysis in traffic videos of high and low quality based on the YOLO model

    Object detection and near-miss analysis in traffic videos of high and low quality based on the YOLO model by Zhu, Wen, Lim, Lek Ming, Majid Khan Majahar Ali, Wu, Lili, Elshahed, Amr

    Published 2025
    “…Considering the expressway scenario in this study, we use manual reporting (based on human detection), the bird’s-eye view method (based on image processing), and the distance neighbor method (based on data analysis) for near-miss detection. …”
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  6. 6
    Long gap imputation in air quality (PM10) data set using improvised EOF-based method with roughness penalty approach / Shamihah Muhammad Ghazali

    Long gap imputation in air quality (PM10) data set using improvised EOF-based method with roughness penalty approach / Shamihah Muhammad Ghazali by Muhammad Ghazali, Shamihah

    Published 2022
    “…Missing values lead to the problem of low accuracy prediction and bias of the analysis results. …”
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  7. 7
    Improving data entry in basketball analysis user interface using HCI usability principles / Hadzri Harman

    Improving data entry in basketball analysis user interface using HCI usability principles / Hadzri Harman by Harman, Hadzri

    Published 2012
    “…The problem occur when user miss capture the data because of doing the data entry process for the previous data. …”
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  8. 8
    Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli

    Revised normal ratio methods for imputation of missing rainfall data / Siti Nur Zahrah Amin Burhanuddin, Sayang Mohd Deni and Norazan Mohamed Ramli by Amin Burhanuddin, Siti Nur Zahrah, Mohd Deni, Sayang, Mohamed Ramli, Norazan

    Published 2016
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  9. 9
    Estimation of Missing Rainfall Data Using Spatial Interpolation and Imputation Methods

    Estimation of Missing Rainfall Data Using Spatial Interpolation and Imputation Methods by Roslinazairimah, Zakaria, Noor Fadhilah, Ahmad Radi, Muhammad Az-Zuhri, Azman

    Published 2015
    “…Alternative method for solving missing data is an imputation method. Imputation is a process of replacing missing data with substituted values. …”
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  10. 10
    Comparison between imputation method for handling missing data / Ayunie Ezadin, Nur Izzaty Chumin and Siti Nur Izzatulnisa Salit

    Comparison between imputation method for handling missing data / Ayunie Ezadin, Nur Izzaty Chumin and Siti Nur Izzatulnisa Salit by Ezadin, Ayunie, Chumin, Nur Izzaty, Salit, Siti Nur Izzatulnisa

    Published 2021
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  11. 11
    An enhanced robust association rules method for missing values imputation in Arabic language data set

    An enhanced robust association rules method for missing values imputation in Arabic language data set by Salem, Awsan Thabet

    Published 2023
    “…The failure to handle missing values usually causes unwanted consequences such as misleading analysis and decision-making. …”
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  12. 12
    Constructing partial least squares model in the presence of missing data

    Constructing partial least squares model in the presence of missing data by Mohd Jamil, Jastini, Mohd Shaharanee, Izwan Nizal

    Published 2015
    “…Virtually all methods of data analysis are plagued by problems with missing data, and partial least squares are no exception.This work contributes to knowledge by critically examining ways of handling missing data in the estimation of Partial Least Squares Models. …”
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  13. 13
    An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data

    An improved imputation method based on fuzzy c-means and particle swarm optimization for missing data by Samat, Nurul Ashikin

    Published 2017
    “…However, if data mining techniques are applied on real datasets, a problem that often comes up is that missing values occur in the datasets. Since the missing values may confuse the data mining process and causing the knowledge extracted unreliable, there is a need to handle the missing values. …”
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  14. 14
    A Study on determinants of Customer Satisfaction Towards Broadband Services in Songkhla Province

    A Study on determinants of Customer Satisfaction Towards Broadband Services in Songkhla Province by Laeheem, Miss Fateemoh

    Published 2012
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  15. 15
    Development of an imputation technique - INI for software metric database with incomplete data

    Development of an imputation technique - INI for software metric database with incomplete data by Wasito, Ito, Olanrewaju, Rashidah F.

    Published 2007
    “…Missing data leads to loss of information, causes biasness in data analysis and hence results to inaccurate decision-making for project management and implementation. …”
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  16. 16
    New and Improved Safety and Risk Assessment Model for Petrol Fuel Station

    New and Improved Safety and Risk Assessment Model for Petrol Fuel Station by Mirza, Munir, Kutty, S.R.M., Azmi , Mohd Shariff, Khamidi, M. Faris

    Published 2011
    “…Measurement of risk levels posed by hazardous activities on organizations assets, entities and processes are of highly significance. This can be done with risk assessment process. …”
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  17. 17
    Imputation of Rainfall Data Using the Sine Cosine Function Fitting Neural Network

    Imputation of Rainfall Data Using the Sine Cosine Function Fitting Neural Network by Chiu, Po Chan, Ali, Selamat, Ondrej, Krejcar, Kuok, King Kuok, Enrique, Herrera-Viedma, Giuseppe, Fenza

    Published 2021
    “…First, we propose a novel pre-processing mechanism for non-precipitation data by using principal component analysis (PCA). …”
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  18. 18
    Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis

    Evaluation of linear interpolation method for missing value on solar radiation dataset in Perlis by Saaban, Azizan, Zainudin, Lutfi, Abu Bakar, Mohd Nazari

    Published 2015
    “…This paper intends to reveal the ability of the linear interpolation method to predict missing values in solar radiation time series. Reliable dataset is equally tends to complete time series observed dataset.The absence or presence of radiation data alters long-term variation of solar radiation measurement values.Based on that change, the opportunities to provide bias output result for modelling and the validation process is higher.The completeness of the observed variable dataset has significantly important for data analysis.Occurrence the lack of continual and unreliable time series solar radiation data widely spread and become the main problematic issue. …”
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  19. 19
    Entrepreneurial leadership learning: in search of missing links

    Entrepreneurial leadership learning: in search of missing links by Bagheri, Afsaneh, Lope Pihie, Zaidatol Akmaliah

    Published 2010
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  20. 20
    Proposed new design scheme for Miss Sixty retail shop at Lot 03- 61,62 63 & 64, Third Floor, Berjaya Times Square, No 1 Jalan Imbi, 55100, Kuala Lumpur / Wan Zurainor Wan Zainun

    Proposed new design scheme for Miss Sixty retail shop at Lot 03- 61,62 63 & 64, Third Floor, Berjaya Times Square, No 1 Jalan Imbi, 55100, Kuala Lumpur / Wan Zurainor Wan Zainun by Wan Zainun, Wan Zurainor

    Published 2006
    “…The purposed of this final project is to realize the design process that involve in the preliminary findings, analysis case study and synthesizing Diploma of Interior Architecture. …”
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