Search Results - (( learning missing learning algorithm ) OR ( java simulation optimization algorithm ))
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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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ExtraImpute: a novel machine learning method for missing data imputation
Published 2022“…In this paper, we propose a new imputation approach using Extremely Randomized Trees (Extra Trees) of machine learning ensemble learning methods named (ExtraImpute) to tackle numerical missing values in healthcare context. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…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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Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm
Published 2021“…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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Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…Missing data is a widespread data quality issue across various domains. …”
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A novel approach for handling missing data to enhance network intrusion detection system
Published 2025“…Our approach employs the Random Missing Value (RMV) algorithm to simulate missing data, enabling thorough testing and comparison of various imputation techniques. …”
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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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Intelligent imputation method for mix data-type missing values to improve data quality
Published 2024“…Missing data is a widespread data quality issue across various domains. …”
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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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Auto-feed hyperparameter support vector regression prediction algorithm in handling missing values in oil and gas dataset
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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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems
Published 2022“…In the performance comparison between proposed deep reinforcement learning with evolutionary algorithm, despite one of the variants of evolutionary algorithm has good performance in precision, it has rather weak performance in term of novelty and diversity. …”
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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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Imputation Analysis of Time-Series Data Using a Random Forest Algorithm
Published 2024“…To address the issue, this paper compared and evaluated four imputation methods: MissForest, MICE, Simplefill, and Softimpute which utilized Random Forest Algorithm. …”
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Federated deep learning for automated detection of diabetic retinopathy
Published 2022“…Federated learning allows deep learning algorithms to learn from a diverse set of data stored in multiple databases. …”
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Proceeding Paper -
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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