cmf_krr_ecvr_pred {conmolfields} | R Documentation |
To make predictions using ecvr results
Description
To make predictions using ecvr results
Usage
cmf_krr_ecvr_pred(ecvr_fname = "ligands-ecvr.RData", kernels_train_fname = "ligands-kernels-train.RData", kernels_pred_fname = "ligands-kernels-pred.RData", act_colnum = 2, sep = ",", act_pred_fname = "activity-pred.txt", pred_fname = "ligands-pred.RData", ...)
Arguments
ecvr_fname |
|
kernels_train_fname |
|
kernels_pred_fname |
|
act_colnum |
|
sep |
|
act_pred_fname |
|
pred_fname |
|
... |
|
Examples
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function (ecvr_fname = "ligands-ecvr.RData", kernels_train_fname = "ligands-kernels-train.RData",
kernels_pred_fname = "ligands-kernels-pred.RData", act_colnum = 2,
sep = ",", act_pred_fname = "activity-pred.txt", pred_fname = "ligands-pred.RData",
...)
{
load(ecvr_fname)
load(kernels_train_fname)
load(kernels_pred_fname)
iprop <- act_colnum
if (iprop > 0) {
act <- read.table(act_pred_fname, header = TRUE, sep = sep)
y_exp <- act[, iprop]
}
else {
y_exp <- NA
}
ecvr_pred <- cmf_krr_ecvr_pred_mem(ecvr = ecvr, kernels = kernels,
kernels_pred = kernels_pred, y_exp = y_exp, ...)
save(ecvr_pred, file = pred_fname)
}
[Package
conmolfields version 0.0-19
Index]