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Table 2 Predicted performances of the selected biosignatures

From: Network and biosignature analysis for the integration of transcriptomic and metabolomic data to characterize leaf senescence process in sunflower

  Metric In Sample Out Sample 95 % Confidence Interval
Metabolites R2 0.997 0.840 [ 0.335, 0.972 ]
Mean Absolute Error 0.228 2.503 [ 0.783, 4.060 ]
Mean Squared Error 0.2104 12.180 [ 0.964, 24.916 ]
Transcription factors R2 0.983 0.825 [ 0.565, 0.939 ]
Mean Absolute Error 0.897 2.658 [ 1.009, 4.950 ]
Mean Squared Error 1.239 13.315 [ 3.743, 29.804 ]
Integrated list R2 0.9965 0.909 [ 0.721, 0.986 ]
Mean Absolute Error 0.465 1.779 [ 0.487, 3.919 ]
Mean Squared Error 0.2639 6.927 [ 0.469, 18.832 ]
  1. Performances are reported in terms of the determination coefficient R2, Mean Absolute Error (MAE) and Mean Squared Error (MSE, see text for more details on these metrics). The in-sample performances quantify the fitness of the predictive models on the training data, while the out-of-sample values estimate the expected performance on new data. Confidence intervals are calculated using a bootstrap approach