Print the predict.cv.ptLasso object.
Usage
# S3 method for class 'predict.cv.ptLasso'
print(x, ...)Examples
# Train data
out = gaussian.example.data(k=2, class.sizes = c(50, 50))
x = out$x; y=out$y; groups = out$group;
# Test data
outtest = gaussian.example.data(k=2, class.sizes = c(50, 50))
xtest=outtest$x; ytest=outtest$y; groupstest=outtest$groups
cvfit = cv.ptLasso(x, y, groups = groups, nfolds = 3, family = "gaussian", type.measure = "mse")
pred = predict(cvfit, xtest, groupstest, ytest=ytest, s="lambda.min")
print(pred)
#>
#> Call:
#> predict.cv.ptLasso(object = cvfit, xtest = xtest, groupstest = groupstest,
#> ytest = ytest, s = "lambda.min")
#>
#>
#> alpha = 0.8
#>
#> Performance (Mean squared error):
#>
#> allGroups mean group_1 group_2 r^2
#> Overall 540.5 540.5 528.3 552.8 0.17213
#> Pretrain 579.7 579.7 568.4 590.9 0.11219
#> Individual 598.8 598.8 578.3 619.3 0.08281
#>
#> Support size:
#>
#> Overall 23
#> Pretrain 11 (0 common + 11 individual)
#> Individual 9
# If ytest is not supplied, just prints the pretrained predictions.
pred = predict(cvfit, xtest, groupstest, s="lambda.min")
print(pred)
#>
#> Call:
#> predict.cv.ptLasso(object = cvfit, xtest = xtest, groupstest = groupstest,
#> s = "lambda.min")
#>
#>
#> alpha = 0.8
#>
#> Support size:
#>
#> Overall 23
#> Pretrain 11 (0 common + 11 individual)
#> Individual 9