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Table 3 Evaluation of the random forest classifier performance in step one of MAI for varying sample size and number of metabolites

From: Mechanism-aware imputation: a two-step approach in handling missing values in metabolomics

Metabolite number and sample size combination Mean accuracy (%) Accuracy 95% CI Mean NRMSE NRMSE 95% CI
p = 50 n = 50 82.0 [80.1%, 83.5%] 0.260 [0.245, 0.278]
p = 50 n = 100 81.8 [80.3%, 83.2%] 0.264 [0.256, 0.278]
p = 100 n = 50 81.3 [80.2%, 82.4%] 0.282 [0.267, 0.282]
p = 200 n = 400 82.1 [80.0%, 83.3%] 0.259 [0.256, 0.263]
p = 400 n = 200 81.7 [80.0%, 82.7%] 0.272 [0.271, 0.272]
p = 50 n = 400 81.7 [80.2%, 82.9%] 0.270 [0.260, 0.270]
p = 400 n = 50 82.0 [80.1%, 83.3%] 0.273 [0.264, 0.288]
p = 400 n = 20 82.1 [80.1%, 82.9%] 0.239 [0.234, 0.245]
  1. Accuracy metrics with associated 95% confidence intervals (Cis) are reported for different combinations of sample size (n) and number of metabolites (p) from the COPDGene Data Set 1