cmf_krr_ecvr_pred: To make predictions using ecvr results
In conmolfields: Continuous molecular fields

To make predictions using ecvr results

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", ...)

`ecvr_fname`
`kernels_train_fname`
`kernels_pred_fname`
`act_colnum`
`sep`
`act_pred_fname`
`pred_fname`
`...`

##---- 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)
  }