Search Results - (( java application optimization algorithm ) OR ( missing value problem algorithm ))
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An Evaluation of Machine Learning Algorithms for Missing Values Imputation
Published 2019“…Hence, it is necessary to resolve this problem of missing values imputation. Our research paper presents a review of missing values imputation approaches. …”
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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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Missing-values imputation algorithms for microarray gene expression data
Published 2019“…In gene expression studies, missing values are a common problem with important consequences for the interpretation of the final data (Satija et al., Nat Biotechnol 33(5):495, 2015). …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Missing values in that attribute were replaced by the mode value. …”
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Missing value estimation methods for data in linear functional relationship model
Published 2017“…Missing value problem is common when analysing quantitative data. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Restoration of missing data in old archives based on genetic algorithm
Published 2014“…In this paper, we consider this task similar to an optimization problem and apply Genetic Algorithm (GA) to each frame. …”
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Fuzzy C means imputation of missing values with ant colony optimization
Published 2020“…This paper proposes a improved method of imputation by employing a new version of Fuzzy c Means (FCM) which hybridized with Evolutionary Algorithm to handle missing values problem. Missing values can be treated by imputing the values. …”
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Development of an imputation technique - INI for software metric database with incomplete data
Published 2007“…In this paper, an imputation technique for imputing missing data based on global-local Modified Singular Value Decomposition (MSVD) algorithm, INI was proposed. …”
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Book Section -
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An enhanced robust association rules method for missing values imputation in Arabic language data set
Published 2023“…In data quality, missing values is one form of data completeness problem faced by people who deal with data. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…The final part of this study is an analysis of missing values for circular variables. Missing values is a common problem that occurs in data collection. …”
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Investigation of the Effects of Imputation Methods for Gene Regulatory Networks Modelling Using Dynamic Bayesian Networks
Published 2016“…Several missing value imputation methods have been developed to overcome the problems. …”
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Book Chapter -
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Data prediction and recalculation of missing data in soft set / Muhammad Sadiq Khan
Published 2018“…Few researchers have worked on data filling and recalculating incomplete soft sets, and the current research focuses on predicting missing values and decision values from non-missing data or aggregates. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…In the final part of the study on the missing value problem in LFRM, the modern imputation techniques, namely the expectation-maximization (EM) algorithm and the expectation-maximization with bootstrapping (EMB) algorithm is proposed. …”
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Thesis