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Table 2 Prediction of PMD

From: Using automated texture features to determine the probability for masking of a tumor on mammography, but not ultrasound

Method MSE R 2 N
Univariate selection 117.0 (8.6) 0.67 (0.02) 132.5 (9.7)
Lasso 111.9 (8.4) 0.69 (0.02) 108.8 (12.9)
Boosting 113.0 (8.6) 0.68 (0.02) 126.1 (8.8)
Random forest 120.2 (9.7) 0.66 (0.03) a
  1. Summary statistics (mean and standard deviation) of mean squared error (MSE) and R 2 obtained from (linear) regression models with selected features, as well as the number of selected features N, are shown. All measurements were obtained by 3-fold cross-validation with 100 repetitions
  2. MSE mean squared error, PMD percentage mammographic density
  3. aThere was no variable selection with random forest