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Table 2 Accuracy of RF and SVM classifiers on the neuronal dataset

From: A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data

Genes selected Accuracy (%)a MCC^
SVM RF SVM RF
All genesb 95.3 76.9 0.91 0.00
GSVA feature enrichment 98.5 76.9 0.87 0.00
sRAP 100 76.9 1.00 0.00
SVM-RFE 100 100 1.00 1.00
RF-based Positive MDA 100 76.9 1.00 0.00
T-test 100 97.0 1.00 0.91
  1. The accuracy of the SVM predictors were obtained from LOO cross validation. SVM and RF classifiers were constructed with each set of data listed in TableĀ 2
  2. aAll percentages are rounded off to three significant figures
  3. bTranscripts with a total expression of zero and/or having more than six samples with expression levels less than one were excluded
  4. ^Matthews correlation coefficient (MCC) rounded to 2 decimal places