| |
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 ]
|
- 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
