Hypothesisa
| SDb
| R-squaredc
| Fd
| Pe
| Stabilityf
| RMSEg
| Q-squaredh
| Pearson-Ri
|
\(R_{pred}^{2}\)
j
|
---|
AAARR.594
|
0.1368
|
0. 9542
|
135.30
|
5.277e
−
017
|
0.4923
|
0.1953
|
0.8268
|
0.9103
|
0.711
|
AAAAR.3017 | 0.1458 | 0.9480 | 118.5 | 2.707e−160 | 0.2039 | 0.2342 | 0.7647 | 0.8112 | 0.678 |
AAAHR.2612 | 0.1455 | 0.9482 | 118.9 | 2.597e−16 | 0.2287 | 0.2517 | 0.6808 | 0.8023 | 0.634 |
AAAAH.7206 | 0.1365 | 0. 9530 | 131.8 | 7.3e−17 | 0.1528 | 0.2532 | 0.7627 | 0.8233 | 0.679 |
-
aHypotheses used in the analyses
-
b(SD) the standard deviation of regression
-
c(R
2) coefficient of determination
-
d(F) the ratio of the model variance to the observed activity variance
-
e(P) significance level of F when treated as a ratio of Chi squared distributions
-
f(Stability) stability of the model predictions to changes in the training set composition
-
g(RMSE) the RMS error in the test set predictions
-
h(Q
2) directly analogous to R
2 but based on the test set predictions
-
i(Pearson-R) value for the correlation between the predicted and observed activity for the test set
-
j(\(R_{pred}^{2}\)) Predictive R
2, Standard deviation of error prediction