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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