Friedman average rank sum test results. by Chenyi Zhu (9383370)

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. …”

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i>_<i>δ</i>) based on this metric. …”

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

“…P <0.05 was considered statistically significant. (B). The MCDM algorithm-Stage 2. Feature Ranking, this stage is the process of using the TOPSIS method to rank features. …”

Steps in the extraction of 14 coordinates from the CT slices for the curved MPR. by Linus Woitke (22783534)

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). …”

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_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP by Xiaofeng Wang (119575)

“…In this study, we propose a novel prediction model based on optimization algorithm and neural network, which can select and rank the most important factors that affect mental health of medical workers. …”