2 天前 - … feature selection combination over existing diagnostic baseline models. We validate
the effectiveness of the PSO algorithm in feature selection … of the feature selection method …

2 天前 - … proposed a novel data analysis approach based on … feature selection (IFS) strategy
was applied to select the optimal reverse REOs by using the support vector machine (SVM). …

6 天前 - … ML methods in the training set, including RF, SVM-RFE and Lasso regression. For
the RF algorithm, we selected … For the SVM-RFE algorithm, we screened the predictors by …

7 天前 - … , texture, and subcellular structure features. Next, the best performing features
were selected as the input for SVM (support vector machine)-based prediction models. These …

8 天前 - … Hyperspectral detection technology, as a novel technique, has become an effective
means for evaluating heavy metal pollution in contaminated areas. However, due to the vast …

9 天前 - … feature dimension and selecting the optimal features. In this study, the discriminative
performances of six feature selection methods, ie, PCA, SVM-… However, the novel method …

9 天前 - … the SVM model method as an example, comparing the model performance differences
before and after feature selection … models after RFE feature selection improved by 0.35 (…

11 天前 - … methods (Normality Scores and SVM with feature mapping) … score approach, our
goal is to create a novel method that, … Finally, the specific selection of SVM among the classical …

12 天前 - … To potentially improve the model performance, we applied two different feature
selection techniques, namely, Boruta and RFE protocol to each feature encoding. Results show …

12 天前 - … (Feature Selection through Redundancy and Synergy Analysis), a novel method for
text … FS-RSA aims to identify an optimal feature subset by considering feature interactions at …