Actual average execution time in seconds for NBC-based wrapper FS and NBC classification.

Figshare2015-12-03 更新40

Performance comparison of the selected features with the SVM Classifier utilizing five-fold stratified cross validation.

分类器优化

特征选择性能评估

Best performance for a C value among the kernel is presented. Highest performances are highlighted, along with the feature set and kernel that achieved it. Evaluation Metrics: Accuracy (ACC), Sensitiv

NIAID Data Ecosystem30

The area under ROC, classification accuracy (as a percentage), sensitivity, and specificity obtained with fMRMR feature selection and naive Bayes classification using leave-one-image-out and three-fold cross-validation techniques.

医学图像分析

特征选择性能评估

The maximum AUC and Ac are highlighted with bold face.

NIAID Data Ecosystem20

Actual average execution time in seconds for KNN-based wrapper FS and KNN classification.

资源简介：

Actual average execution time in seconds for KNN-based wrapper FS and KNN classification.

资源简介：

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