Search Results - (( data replication methods algorithm ) OR ( variables selection method algorithm ))
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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Dynamic replication algorithm in data grid: Survey
Published 2008“…For improving the performance of file accesses and to ease the sharing amongst distributed collaboration, such a system needs replication services. Data replication is a common method used to improve the performance of data access in distributed systems. …”
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Enhanced replication strategy with balanced quorum technique and data center selection method in cloud environment
Published 2022“…In order to mitigate the issues, ‘cloud data replication’ is commonly implemented for better data performance and promising business continuity. …”
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Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property
Published 2013“…The experiments were replicated on three different treatments based on removal of outliers and transformation of variables with high value of skewness. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025Subjects:Conference paper -
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The motivation of implementation is to make sure the data replication is easy to maintain and cost effective. …”
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers
Published 2016“…To overcome the instability selection problem, a stability selection approach is put forward to enhance the performance of single-split variable selection method. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…There are many types of motion estimation method but the most used method is the block matching method which is the fixed block matching and the variable block matching. …”
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Enhancing Model Selection Based On Penalized Regression Methods And Empirical Mode Decomposition
Published 2021“…The penalized regularization methods are statistical techniques used to regularize and select the necessary predictor variables that have substantial effects on the response variable. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Evolutionary computation (EC) is known to be an effective search and optimization method and in this paper EC is proposed as a model structure selection algorithm. …”
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New selection algorithm for Mengubah Destini Anak Bangsa (MDAB) students / Zamali Tarmudi ... [et al.]
Published 2014“…This research introduces a new algorithm to select students from low income family the so-called Mengubah Destini Anak Bangsa (MDAB) using fuzzy approach. …”
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Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm
Published 2023“…This study proposes a new wavelength selection method, interval flower pollination algorithm (iFPA), for spectral variable selection in the partial least squares regression (PLSR) model. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…Sure screening-based correlation methods are popular tools used to select the most significant variables in the true model in sparse and high dimensional analysis. …”
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Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)
Published 2021“…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection
Published 2024“…Moreover, selecting the relevant variables when fitting the regression model is critical. …”
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Feature selection methods for optimizing clinicopathologic input variables in oral cancer prognosis
Published 2011“…However, due to time, cost and tissue limitations, the number of prognosis variables need to be reduced. In this research, we demonstrated the use of feature selection methods to select a subset of variables that is highly predictive of oral cancer prognosis. …”
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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…In enhancing prediction accuracy, the T-method employed Taguchi�s orthogonal array as a variable selection approach to determine a subset of independent variables that are significant toward the dependent variable or output. …”
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