Description Usage Arguments Value Author(s)
calculate the cost in psi-Learn with ridge penalty and TLP penalty
1 |
X |
n by p input matrix. |
A |
a vector of n entries coded 1 and -1 for the treatment assignments. |
R |
a vector of outcome variable, larger is more desirable. |
wt |
a vector of weights for each observation. |
w |
coefficients for the decision function, the first element is the bias |
tau |
tuning parameter for the loss function in psi-Learn |
kappa |
tunning parameter to control the complexity of the decision function in the ridge penaly |
lambda |
tunning parameter to control the complexity of the decision function in the TLP penalty |
tau2 |
tunning parameter to control in margin in the TLP penalty |
kernel |
kernel function for pai-Learn, can be 'linear' or 'rbf' (radial basis kernel), default is 'linear'. |
It returns the cost value in psi-Learn
cost |
the cost value in psi-Learn |
MingyangLiu <[email protected]>
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