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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

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

“…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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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.

“…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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Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm by Sophian, Ali, Azmi, Nur Hanisah, Bawono, Ali Aryo

“…In this work, preliminary study of the implementation of one of the latest deep learning algorithms, i.e. YOLOv5, has been carried out in the detection and classification of missing road lane markings. …”
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Imputation Analysis of Time-Series Data Using a Random Forest Algorithm by Nur Najmiyah, Jaafar, Muhammad Nur Ajmal, Rosdi, Khairur Rijal, Jamaludin, Faizir, Ramlie, Habibah, Abdul Talib

“…Missing data poses a significant challenge in extensive datasets, particularly those containing time-series information, leading to potential inaccuracies in data analysis and machine learning model development. …”
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A particle swarm optimization levy flight algorithm for imputation of missing creatinine dataset by Ismail, Amelia Ritahani, Abdul Aziz, Normaziah, Md Ralib, Azrina, Zainal Abidin, Nadzurah, Basath, Samar Salem

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Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

“…The significance of this research is to develop an intelligent method that can deal with both missing values and accuracy in large datasets while minimizing time consumed. …”
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Intelligent imputation method for mix data-type missing values to improve data quality by Alabadla, Mustafa R. A.

“…The significance of this research is to develop an intelligent method that can deal with both missing values and accuracy in large datasets while minimizing time consumed. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

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An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa by Muhd Suberi, Anis Azwani

“…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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Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network by Dayang Suhaila, Awang Suhaili

“…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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Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours by Baneamoon, Saeed Mohammed Saeed

“…An enhanced Bucket Brigade Algorithm (BBA) is developed to avoid the problem of choosing classifiers with high strength value but with incorrect behaviour. …”
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Federated deep learning for automated detection of diabetic retinopathy by Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani

“…Federated learning allows deep learning algorithms to learn from a diverse set of data stored in multiple databases. …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

“…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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Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting by Loh, Eng Chuen

“…Next, a newly developed hybrid deep learning (DL) algorithm is proposed to predict the daily water level in selected rivers that flow through Kelantan. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

“…These factors include identifying relevant atmospheric features contributing to rainfall, addressing missing data, and developing a significant model to predict daily rainfall intensity using appropriate machine-learning techniques. …”
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A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…Missing data is a pervasive challenge in diverse datasets accross various domains. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

“…The system takes the advantage of the past trajectory information to compensate for the missing information during disconnections. A novel decision support system (DSS) is devised with the ability of learning decisional as well as kinematical behaviors of intelligent travelers. …”
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