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Number of classifiers successfully detected the gene as imprinted.

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数据链接：

https://figshare.com/articles/dataset/Number_of_classifiers_successfully_detected_the_gene_as_imprinted_/8238425 数据链接链接失效反馈

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资源简介：

Number of classifiers successfully detected the gene as imprinted.

应用场景：

创建时间：

2019-06-06

随机森林参数调优

分类器性能评估

AUC results for low p/n data. Low p/n results for prediction accuracy using AUC as the performance metric for non-cross-validation results, 10-fold cross-validation and stratified 10-fold cross-valida

NIAID Data Ecosystem60

Leave-one-out cross-validation results.

分类器性能评估

自学习分类器

Recall, precision, and f-measure are calculated for each class. Weighted f-measure, fW, and average accuracy, Acc, are calculated for all classes of a problem. All assessments are based on leave-one-o

NIAID Data Ecosystem50

Confusion matrix for a hypothetical classifier.

分类器性能评估

混淆矩阵

In this table, rows indicate the true class and columns indicate the predicted class. The entries in the table describe the number of observations of each type. When computing the F1 score for this cl

Figshare2021-03-11 更新40

The Cost-Effectiveness of Reclassification Sampling for Prevalence Estimation

流行病学抽样方法

分类器性能评估

BackgroundTypically, a two-phase (double) sampling strategy is employed when classifications are subject to error and there is a gold standard (perfect) classifier available. Two-phase sampling involv

NIAID Data Ecosystem60

A battery of metrics of five classifiers in the training and validation cohorts for fivefold nested cross-validation.

分类器性能评估

交叉验证

A battery of metrics of five classifiers in the training and validation cohorts for fivefold nested cross-validation.

NIAID Data Ecosystem40