Table 2 Most important five features for each of the eight feature preselection methods.
From: Assessing preoperative risk of STR in skull meningiomas using MR radiomics and machine learning
Feature pre-selection method | Rank of feature importance | ||||
|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | |
Stepwise logistic | Tumor shape: irregular or regular | Tumor location: convexity | Tumor location: falx | orig.shape.Elongation | fd_vs_re: first diagnose or relapse |
Lasso | Tumor shape: irregular or regular | Tumor location: skull base | orig.shape.Elongation | fd_vs_re: first diagnose or relapse | Tumor location: posterior fossa |
Ridge | Tumor shape: irregular or regular | Tumor location: convexity | Tumor location: falx | Tumor location: skull base | orig,shape,Elongation |
GBM | Tumor shape: irregular or regular | Tumor location: skull base | Tumor location: convexity | orig,glszm.SizeZone NonUniformity | orig,shape,Elongation |
Random forest | Tumor location: convexity | Tumor location: skull base | orig.glszm.SizeZone NonUniformity | Shape: irregular or regular | fd_vs_re: first diagnose or relapse |
Bagged trees | Tumor location: skull base | Tumor location: convexity | orig.shape.Sphericity | Shape: irregular or regular | orig.shape.Elongation |
LDA | Tumor shape: irregular or regular | Tumor location: convexity | Tumor location: skull base | KPI | orig.glszm.Small AreaEmphasis |
Naive Bayes | Tumor shape: irregular or regular | Tumor location: convexity | Tumor location: skull base | KPI | orig.glszm.Small AreaEmphasis |
