Relative performance of classification algorithms using gene-expression and clinical predictors and performing feature selection. حسب Stephen R. Piccolo (8367780)

"…<p>We predicted patient states using gene-expression and clinical predictors with feature selection (Analysis 5). …"

Gene-set overlap results for top 50 genes according to average rank across feature-selection algorithms for GSE46691. حسب Stephen R. Piccolo (8367780)

Gene-set overlap results for top 50 genes according to average rank across feature-selection algorithms for GSE10320. حسب Stephen R. Piccolo (8367780)

Top 50 genes according to average rank across feature-selection algorithms for GSE10320 and GSE46691. حسب Stephen R. Piccolo (8367780)

Illustration of the BRIDES algorithm and the selection process. حسب Cindy Bouchard (6844979)

الموضوعات:

DE algorithm flow. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

Test results of different algorithms. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing feature selection. حسب Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing feature selection with hyperparameter optimization. حسب Stephen R. Piccolo (8367780)

Key gene identification based on two machine learning algorithms. حسب Lijun Guo (605276)

Data_Sheet_3_Strategies to Assure Optimal Trade-Offs Among Competing Objectives for the Genetic Improvement of Soybean.docx حسب Vishnu Ramasubramanian (4951354)

Data_Sheet_7_Strategies to Assure Optimal Trade-Offs Among Competing Objectives for the Genetic Improvement of Soybean.docx حسب Vishnu Ramasubramanian (4951354)

Data_Sheet_2_Strategies to Assure Optimal Trade-Offs Among Competing Objectives for the Genetic Improvement of Soybean.ZIP حسب Vishnu Ramasubramanian (4951354)

Data_Sheet_4_Strategies to Assure Optimal Trade-Offs Among Competing Objectives for the Genetic Improvement of Soybean.xlsx حسب Vishnu Ramasubramanian (4951354)

Data_Sheet_6_Strategies to Assure Optimal Trade-Offs Among Competing Objectives for the Genetic Improvement of Soybean.docx حسب Vishnu Ramasubramanian (4951354)

Data_Sheet_1_Strategies to Assure Optimal Trade-Offs Among Competing Objectives for the Genetic Improvement of Soybean.PDF حسب Vishnu Ramasubramanian (4951354)

Data_Sheet_5_Strategies to Assure Optimal Trade-Offs Among Competing Objectives for the Genetic Improvement of Soybean.xlsx حسب Vishnu Ramasubramanian (4951354)

DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF حسب Deniz Seçilmiş (13028616)

DataSheet1_Optimal Sparsity Selection Based on an Information Criterion for Accurate Gene Regulatory Network Inference.PDF حسب Deniz Seçilmiş (13028616)

UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms. حسب Fatemeh Keikha (20917848)