Search Results - (( variable regression modified algorithm ) OR ( java application customization algorithm ))
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Statistical modeling via bootstrapping and weighted techniques based on variances
Published 2018“…This data will be applied to the multiple logistic regression algorithm and modified Bayesian logistic regression. …”
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Comparing three methods of handling multicollinearity using simulation approach
Published 2006“…In regression, the objective is to explain the variation in one or more response variables, by associating this variation with proportional variation in one or more explanatory variables. …”
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A Comparative Study On Some Methods For Handling Multicollinearity Problems
Published 2006“…In regression, the objective is to explain the variation in one or more response variables, by associating this variation with proportional variation in one or more explanatory variables. …”
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A comparative study on some methods for handling multicollinearity problems
Published 2006“…In regression, the objective is to explain the variation in one or more response variables, by associating this variation with proportional variation in one or more explanatory variables. …”
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Water Quality Index Using Modified Random Forest Technique: Assessing Novel Input Features
Published 2024journal::journal article -
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Comparison between fuzzy bootstrap weighted multiple linear regression and multiple linear regression: a case study for oral cancer modelling
Published 2018“…Three different SAS algorithms (i) bootstrap multiple linear regression (BMLR), (ii) bootstrap weighted Bayesian multiple linear regression (BWBMLR), and (iii) fuzzy bootstrap weighted multiple linear regression (FBWMLR) were compared separately according to their average width of prediction. …”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…The data for training and testing the algorithms was derived using the regression equation developed using the Box-Behnken Design (BBD). …”
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Identification of suitable explanatory variable in goldfeld-quandt test and robust inference under heteroscedasticity and high leverage points
Published 2016“…This study has developed an algorithm of identifying this variable prior to conducting the Goldfeld-Quandt test in multiple linear regression model. …”
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Robust Estimation Methods And Outlier Detection In Mediation Models
Published 2010“…Mediation models refer to the relationships among three variables: an independent variables (IV), a potential mediating variable (M), and a dependent variable (DV). …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering
Published 2019“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Predicting motorcycle customization preferences using machine learning
Published 2025“…The classification model was developed using the Random Forest algorithm, Support Vector Machine and Logistic Regression with 5-fold Cross validation. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…And the few existing ones that can work for regression tasks were recently found to underestimate mutual information between two strongly dependent variables. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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