
<pre><code>## family:    gaussian 
## loss:      sq_loss_lasso 
## method:    weighting 
## cutpoint:  0 
## augmentation 
## function: augment.func 
## propensity 
## function:  propensity.func 
## 
## benefit score: f(x), 
## Trt recom = 1*I(f(x)&gt;c)+0*I(f(x)&lt;=c) where c is &#39;cutpoint&#39;
## 
## Average Outcomes:
##                Recommended 0     Recommended 1
## Received 0   9.571 (n = 103) -7.8823 (n = 102)
## Received 1 -2.2994 (n = 120)   0.008 (n = 175)
## 
## Treatment effects conditiona