Simulation results of networks selection in multinormial logistic regression and edge selection in network estimation, where GNmC: GRN-multiClassifier, prNW: multi-class classification model grounded in a pre-estimated network, Classification results based on expression levels by using LA: lasso, ELA: elastic net, KSVM: kernelized support vector machine, RF: random forest.
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https://figshare.com/articles/dataset/Simulation_results_of_networks_selection_in_multinormial_logistic_regression_and_edge_selection_in_network_estimation_where_GNmC_GRN-multiClassifier_prNW_multi-class_classification_model_grounded_in_a_pre-estimated_network_Classification_re/28963531
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资源简介：
Simulation results of networks selection in multinormial logistic regression and edge selection in network estimation, where GNmC: GRN-multiClassifier, prNW: multi-class classification model grounded in a pre-estimated network, Classification results based on expression levels by using LA: lasso, ELA: elastic net, KSVM: kernelized support vector machine, RF: random forest.
创建时间：
2025-05-08
