Table 1. The parameters of linear regression equations that predict the values of ω_{n+} and log(С_{n/m})obtained during learning and in the leaveoneout procedure.
Set number 
Note 
Predicted value 
n 
R^{2}_{L} 
SEM_{L} 
Q^{2} 
SEM_{LOO} 
1. 
Variant 1 
ω_{1+} 
557 
0.2 
0.031 
 
 
2. 
Variant 1 
ω_{2+} 
557 
0.53 
0.208 
0.5 
0.214 
3. 
Variant 1 
ω_{3+} 
557 
0.35 
0.229 
 
 
4. 
Variant 1 
ω_{4+} 
557 
0.29 
0.08 
 
 
5. 
Variant 2 
ω_{1+} 
148 
0.45 
0.44 
0.3 
0.051 
6. 
Variant 2 
ω_{2+} 
300 
0.64 
0.153 
0.59 
0.162 
7. 
Variant 2 
ω_{3+} 
177 
0.47 
0.107 
0.29 
0.130 
8. 
Variant 2 
ω_{4+} 
29 
 
 
 
 
9. 
log(C_{1/2}) 
148 
0.65 
0.183 
0.51 
0.216 

10. 

log(C_{2/3}) 
161 
0.55 
0.384 
0.45 
0.42 
11. 

log(C_{3/4}) 
25 
 
 
 
 
Note. R^{2}_{L}: R^{2} in the learning procedure; SEM_{L}: standard error of the mean in the learning procedure; n: number of observation in the learning procedure; Q^{2}: Q^{2} in the leaveoneout procedure; SEM_{LOO}: standard error of the mean in the leaveoneout procedure. Variant 1: the observation with values 0 or 1 were used. Variant 2: the observation with the values 0 or 1 were omitted. The calculations were not performed if the number of observations was less than 60 or R^{2} in the learning procedure was less than 0.4.