To make predictiokns
cmf_krr_pred(model_fname = "ligands-model.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", ...)
model_fname | |
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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 (model_fname = "ligands-model.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(model_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 } y_pred <- cmf_krr_pred_mem(model = model, kernels = kernels, kernels_pred = kernels_pred, y_exp = y_exp, ...) pred <- list(y_pred = y_pred, y_exp = y_exp) save(pred, file = pred_fname) pred }#> function (model_fname = "ligands-model.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(model_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 #> } #> y_pred <- cmf_krr_pred_mem(model = model, kernels = kernels, #> kernels_pred = kernels_pred, y_exp = y_exp, ...) #> pred <- list(y_pred = y_pred, y_exp = y_exp) #> save(pred, file = pred_fname) #> pred #> } #> <environment: 0x109648540>