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Systematic review on missing data imputation techniques with machine learning algorithms for healthcare
Published 2022“…Many machine learning algorithms have been applied to impute missing data with plausible values. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…A common challenge is the occurrence of missing data during the data input process. Numerous studies have proposed methods to impute missing values for data across multiple fields. …”
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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
Published 2020“…This can significantly affect the prediction results and making it less accurate due to missing value and become a challenging issue. Missing values in datasets is a synonymous problem in data mining which could lead to an incomplete dataset, making inaccurate predictions results in machine learning prediction processes. …”
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Intelligent imputation method for mix data-type missing values to improve data quality
Published 2024“…A common challenge is the occurrence of missing data during the data input process. Numerous studies have proposed methods to impute missing values for data across multiple fields. …”
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Extreme learning machine classification of file clusters for evaluating content-based feature vectors
Published 2018“…In the digital forensic investigation and missing data files retrieval in general, there is a challenge of recovering files that have missing system information. …”
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Classification of JPEG files by using extreme learning machine
Published 2018“…This paper proposes an Extreme Learning Machine (ELM) algorithm to assign a class label of JPEG or Non-JPEG image for files in a continuous series of data clusters. …”
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Machine learning model for performance prediction in mobile network management / Muhammad Hazim Wahid
Published 2022“…One of the major challenges when applying machine learning is to identify the best algorithm from a variety of algorithms to solve a problem. …”
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Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network
Published 2006“…The back propagation algorithm was adopted for this study. The optimal model for predicting missing data found in this study is the network with the combination of learning rate and the number of neurons in the hidden layer of 0.2 and 60. …”
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Final Year Project Report / IMRAD -
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model
Published 2023“…The algorithm detects the affected region depending on pixel similarity computation process. …”
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Evaluation of Convolutional Neural Network based on Dental Images for Age Estimation
Published 2023Conference Paper -
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Super resolution imaging using modified lanr based on separable filtering
Published 2019“…Reaching super resolution has been a challenge in image processing practices, because of their under-constrained nature that requires the missing HR image details to be reconstructed. …”
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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…Missing data is a pervasive challenge in diverse datasets accross various domains. …”
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An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa
Published 2020“…The results demonstrate that the performance measure of 90.77% has been recorded for detection rate with average processing time of 1.02 to 1.04 seconds per image. The developed algorithm is reported to be reliable to assist the radiologist in ischemic PF diagnosis which is important for future healthcare needs.…”
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Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours
Published 2010“…Overall, the enhanced approaches performed well and the enhanced learning processes proposed in the current study makes robot learning more effective. …”
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An adaptive opposition-based learning selection: The case for jaya algorithm
Published 2021“…Over the years, opposition-based Learning (OBL) technique has been proven to effectively enhance the convergence of meta-heuristic algorithms. …”
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Predictive analytics for the sentiment of malaysian place of interest using machine learning models
Published 2023“…Additionally, several Natural Language Processing (NLP) techniques were employed to pre-process the text data, as part of the machine learning process. …”
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Undergraduates Project Papers -
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…Adding the uncertain class the best accuracy obtained was 98.5% using the SMO algorithm. A predictive classification model that determines the accuracy for three classification classes was developed accordingly using the SMO algorithm.…”
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