The confidence change of the binary image after iteration. by Dingming Yang (8505990)

Table1_Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.docx by Haohan Xue (17892128)

“…The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. …”

DataSheet1_Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.ZIP by Haohan Xue (17892128)

“…The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. …”

Image_2_A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms.TIF by Qingqing Li (1505614)

“…First, we used the Fast Correlation-Based Filter (FCBF) algorithm to filter a large number of irrelevant and redundant genes in the raw dataset, and then used the wrapper feature selection method based on the he Multi-layer Perceptron (MLP) neural network and the Particle Swarm Optimization (PSO), accuracy (ACC) and mean square error (MSE) were then used as the evaluation criteria. …”

Image_1_A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms.TIF by Qingqing Li (1505614)

“…First, we used the Fast Correlation-Based Filter (FCBF) algorithm to filter a large number of irrelevant and redundant genes in the raw dataset, and then used the wrapper feature selection method based on the he Multi-layer Perceptron (MLP) neural network and the Particle Swarm Optimization (PSO), accuracy (ACC) and mean square error (MSE) were then used as the evaluation criteria. …”

Image_3_A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms.TIF by Qingqing Li (1505614)

“…First, we used the Fast Correlation-Based Filter (FCBF) algorithm to filter a large number of irrelevant and redundant genes in the raw dataset, and then used the wrapper feature selection method based on the he Multi-layer Perceptron (MLP) neural network and the Particle Swarm Optimization (PSO), accuracy (ACC) and mean square error (MSE) were then used as the evaluation criteria. …”

<i>FS</i> index of KNN on the selected feature subset. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

<i>ACC</i> index of KNN on the selected feature subset. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

<i>FS</i> index of SVM on the selected feature subset. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

The flowchart of the IG-GPSO. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

<i>ACC</i> index of SVM on the selected feature subset. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

Unraveling Adsorbate-Induced Structural Evolution of Iron Carbide Nanoparticles by Peter S. Rice (11805875)

“…Here, using a combined density functional theory (DFT), neural network interatomic potential-assisted global optimization, and ensemble learning study, we evaluate dynamic surface changes associated with syngas (H and CO) interactions. …”

The overview of the proposed method. by Sepideh Zununi Vahed (9861298)

GSE96058 information. by Sepideh Zununi Vahed (9861298)

“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”

The performance of classifiers. by Sepideh Zununi Vahed (9861298)

“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”

Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... by Uttam Khatri (12689072)

“…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …”