five

Carbohydrate binding site prediction accuracy benchmarks for 10-fold cross validations and independent tests.

收藏
NIAID Data Ecosystem2026-03-07 收录
下载链接:
https://figshare.com/articles/dataset/_Carbohydrate_binding_site_prediction_accuracy_benchmarks_for_10_fold_cross_validations_and_independent_tests_/274189
下载链接
链接失效反馈
官方服务:
资源简介:
The carbohydrate binding site predictions were carried out with the ANN, SVM and ANN_BAGGING algorithm on the proteins from the S497 dataset and the prediction accuracy of the ANN_BAGGING on the independent test set S108. Matthews correlation coefficient (MCC), F-score(Fsc), Accuracy(Acc), Precision(Pre), Sensitivity(Sen) and Specificity(Spe) are shown in Equations (4)∼(9). The benchmarks for the ten-fold cross validation results (i.e., S497/ANN, S497/SVM, and S497/ANN_BAGGING) are shown in two ways: The values enclosed in parenthesis are the averaged benchmark value and standard deviation calculated from the ten-fold results; the values above the average±standard-deviation pairs are the overall benchmark values calculated with the combined TP, TN, FP, FN cases from the test sets of the ten-fold cross-validation results.
创建时间:
2012-07-25
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作