Search Results - "Yahya Algamal, Zakariya"
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1
Improving binary crow search algorithm for feature selection
Published in Journal of intelligent systems (16-02-2023)“…The feature selection (FS) process has an essential effect in solving many problems such as prediction, regression, and classification to get the optimal…”
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Enhancement of K-means clustering in big data based on equilibrium optimizer algorithm
Published in Journal of intelligent systems (16-02-2023)“…Data mining’s primary clustering method has several uses, including gene analysis. A set of unlabeled data is divided into clusters using data features in a…”
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3
Developing a ridge estimator for the gamma regression model
Published in Journal of chemometrics (01-10-2018)“…The ridge regression model has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The gamma…”
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4
Shrinkage parameter selection via modified cross-validation approach for ridge regression model
Published in Communications in statistics. Simulation and computation (02-07-2020)“…The ridge regression estimator has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The choice…”
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5
Performance of ridge estimator in inverse Gaussian regression model
Published in Communications in statistics. Theory and methods (03-08-2019)“…The presence of multicollinearity among the explanatory variables has undesirable effects on the maximum likelihood estimator (MLE). Ridge estimator (RE) is a…”
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Liu-type estimator for the gamma regression model
Published in Communications in statistics. Simulation and computation (02-08-2020)“…In this paper, we propose a new biased estimator called Liu-type estimator in gamma regression models in the presence of collinearity. We also consider some…”
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Improved estimators in bell regression model with application
Published in Journal of statistical computation and simulation (12-08-2024)“…In this paper, we propose the application of shrinkage strategies to estimate coefficients in the Bell regression models when prior information about the…”
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8
A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification
Published in Advances in data analysis and classification (01-09-2019)“…The common issues of high-dimensional gene expression data are that many of the genes may not be relevant, and there exists a high correlation among genes…”
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9
Developing a Liu‐type estimator in beta regression model
Published in Concurrency and computation (28-02-2022)“…The beta regression model is a commonly used when the response variable has the form of fractions or percentages. The maximum likelihood (ML) estimator is used…”
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Improving Harris hawks optimization algorithm for hyperparameters estimation and feature selection in v‐support vector regression based on opposition‐based learning
Published in Journal of chemometrics (01-11-2020)“…Many real problems have been solved by support vector regression, especially v‐support vector regression (v‐SVR), but there are hyperparameters that usually…”
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11
Tuning parameter estimation in SCAD-support vector machine using firefly algorithm with application in gene selection and cancer classification
Published in Computers in biology and medicine (01-12-2018)“…In cancer classification, gene selection is one of the most important bioinformatics related topics. The selection of genes can be considered to be a variable…”
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12
Bias reduction of maximum likelihood estimation in exponentiated Teissier distribution
Published in Frontiers in applied mathematics and statistics (20-03-2024)“…The exponentiated Teissier distribution (ETD) offers an alternative for modeling survival data, taking into account flexibility in modeling data with…”
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13
Gene selection for microarray gene expression classification using Bayesian Lasso quantile regression
Published in Computers in biology and medicine (01-06-2018)“…Gene selection has been proven to be an effective way to improve the results of many classification methods. However, existing gene selection techniques in…”
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14
Least absolute deviation estimator‐bridge variable selection and estimation for quantitative structure–activity relationship model
Published in Journal of chemometrics (01-07-2019)“…Regression models are frequently encountered in many scientific fields, especially in quantitative structure–activity relationship (QSAR) modeling. The…”
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IMPROVING PARAMETERS OF V-SUPPORT VECTOR REGRESSION WITH FEATURE SELECTION IN PARALLEL BY USING QUASI-OPPOSITIONAL AND HARRIS HAWKS OPTIMIZATION ALGORITHM
Published in Informatyka, automatyka, pomiary w gospodarce i ochronie środowiska (30-06-2024)“…Numerous real-world problems have been addressed using support vector regression, particularly v-support vector regression (v-SVR), but some parameters need to…”
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16
Variable selection in Poisson regression model based on chaotic meta-heuristic search algorithm
Published in BIO web of conferences (01-01-2024)“…By determining the most significant variables that are connected to the response variable, Increasing prediction accuracy and processing speed can be achieved…”
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A New Two-Parameter Estimator for Beta Regression Model: Method, Simulation, and Application
Published in Frontiers in applied mathematics and statistics (26-01-2022)“…The beta regression is a widely known statistical model when the response (or the dependent) variable has the form of fractions or percentages. In most of the…”
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Boosting Arithmetic Optimization Algorithm with Genetic Algorithm Operators for Feature Selection: Case Study on Cox Proportional Hazards Model
Published in Mathematics (Basel) (01-09-2021)“…Feature selection is a well-known prepossessing procedure, and it is considered a challenging problem in many domains, such as data mining, text mining,…”
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Gene selection and classification of microarray gene expression data based on a new adaptive L1-norm elastic net penalty
Published in Informatics in medicine unlocked (2021)“…The removal of irrelevant and insignificant genes has always been a major step in microarray data analysis. The application of gene selection methods in…”
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Modified jackknife ridge estimator for the Conway-Maxwell-Poisson model
Published in Scientific African (01-03-2023)“…Recently, research papers have shown a strong interest in modeling count data. The over-dispersion or under-dispersion are frequently seen in the count data…”
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