Skip to main content
Fig. 4 | BMC Medical Informatics and Decision Making

Fig. 4

From: Multiple machine-learning tools identifying prognostic biomarkers for acute Myeloid Leukemia

Fig. 4

Screening important genes related to the prognosis of AML patients based on recursive feature elimination (RFE) algorithm. Feature selection is performed using multiple functions in the R package caret (lrFuncs, IdaProfile, caretFuncs, and nbFuncs). (A) lrFuncs model identified 15 genes as the optimal characteristic genes (maximum accuracy = 0.9595). (B) 26 genes were identified as the optimal feature genes by the IdaProfile model (maximum accuracy = 0.9595); (C) caretFuncs model identified 12 genes as the optimal characteristic genes (maximum accuracy = 0.9853); (D) nbFuncs model identified 24 genes as the optimal feature genes (maximum accuracy = 0.8856)

Back to article page