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Table 3 Evaluation metrics for marker sets on experimental data. The “Average precision” metric is a weighted average of precision over the clusters. The Matthews correlation coefficient is a summary statistic that incorporates all information from the confusion matrix. See [22] for more information about the classification metrics and [23] for more information about the clustering metrics

From: A rank-based marker selection method for high throughput scRNA-seq data

General procedure Methods Metrics
Supervised classification Nearest centroid classifier (NCC)Random forests classifier (RFC) Classification error (1 - accuracy)
   Average precision
   Matthews correlation coefficient
Unsupervised clustering Louvain clustering Adjusted rand index (ARI)
   Adjusted mutual information (AMI)
   Fowlkes-Mallows score (FMS)