Search Results - (( java applications optimized algorithm ) OR ( missing value (problems OR 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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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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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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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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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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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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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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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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Conference or Workshop Item -
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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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Solving nonlinear system of third-order boundary value problems using block method
Published 2014“…In this paper, we propose an algorithm of two-point block method to solve the nonlinear system of third-order boundary value problems directly. …”
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Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours
Published 2010“…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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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…Data incomplete is happened when some of data to process is missing so it failed to record it. Problem of the size of data happen when data cannot be process because of it too complex. …”
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Undergraduates Project Papers -
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Hybrid Sine Cosine and Fitness Dependent Optimizer for global optimization
Published 2021“…Additionally, the SC-FDO was applied to the missing data estimation cases and refined the missingness as optimization problems. …”
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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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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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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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