Description Usage Arguments Value Author(s) See Also Examples
View source: R/fitted.glmnetcr.R
For a given step, returns the AIC, BIC, predicted class, and the fitted probabilities for the K classes.
1 2 |
object |
a |
newx |
a data matrix representing the predictor variables, if missing defaults to original data used in fitting the model |
s |
the step at which the fitted probabilities and class are desired |
... |
additional optional arguments |
AIC |
AIC at step s |
BIC |
BIC at step s |
class |
a vector of length n indicating the predicted class for each observation in newx at step s |
probs |
a matrix with n rows and K columns indicating the fitted class probabilities for each observation and class in new at step x |
Kellie J. Archer, archer.43@osu.edu
See Also as predict.glmnetcr
, select.glmnetcr
1 2 3 4 5 |
Loading required package: glmnet
Loading required package: Matrix
Loading required package: foreach
Loaded glmnet 2.0-16
Warning message:
from glmnet Fortran code (error code -26); Convergence for 26th lambda value not reached after maxit=100 iterations; solutions for larger lambdas returned
$BIC
s23
33.76674
$AIC
s23
29.05452
$class
[1] "control" "control"
[3] "control" "control"
[5] "control" "control"
[7] "control" "control"
[9] "impaired fasting glucose" "control"
[11] "impaired fasting glucose" "impaired fasting glucose"
[13] "impaired fasting glucose" "impaired fasting glucose"
[15] "impaired fasting glucose" "type 2 diabetes"
[17] "type 2 diabetes" "type 2 diabetes"
[19] "type 2 diabetes" "type 2 diabetes"
[21] "type 2 diabetes" "type 2 diabetes"
[23] "type 2 diabetes" "type 2 diabetes"
$probs
control impaired fasting glucose type 2 diabetes
[1,] 0.637759660 0.2968232 0.06541710
[2,] 0.742789960 0.2154169 0.04179319
[3,] 0.684967374 0.2608598 0.05417284
[4,] 0.823974148 0.1494688 0.02655706
[5,] 0.678639532 0.2657438 0.05561666
[6,] 0.724791677 0.2297116 0.04549669
[7,] 0.711520081 0.2401679 0.04831200
[8,] 0.721282138 0.2324838 0.04623405
[9,] 0.184716536 0.5184572 0.29682629
[10,] 0.484526771 0.4040373 0.11143589
[11,] 0.133808976 0.5043899 0.36180108
[12,] 0.162057619 0.5146922 0.32325022
[13,] 0.106676146 0.4864906 0.40683329
[14,] 0.188845436 0.5187891 0.29236544
[15,] 0.208919007 0.5190637 0.27201725
[16,] 0.022632656 0.3065999 0.67076742
[17,] 0.024619264 0.3163697 0.65901106
[18,] 0.010433956 0.2251335 0.76443251
[19,] 0.008090478 0.2021177 0.78979178
[20,] 0.024136568 0.3140570 0.66180641
[21,] 0.007500334 0.1956351 0.79686456
[22,] 0.024556421 0.3160707 0.65937286
[23,] 0.012003293 0.2386296 0.74936710
[24,] 0.007139356 0.1915041 0.80135657
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