eval_batchwise: Evaluate fitted ontram models

In LucasKookUZH/ontram-pkg: Ordinal transformation model neural networks

Evaluate fitted ontram models

Description

Evaluate fitted ontram models

Usage

eval_batchwise(model, x, y, im, bs, target)

Examples

data("wine", package = "ordinal")
fml <- rating ~ temp + contact
x_train <- model.matrix(fml, data = wine)[, -1L]
y_train <- model.matrix(~ 0 + rating, data = wine)
x_valid <- x_train[1:20,]
y_valid <- y_train[1:20,]
mo <- ontram_polr(x_dim = ncol(x_train), y_dim = ncol(y_train),
    method = "logit", n_batches = 10, epochs = 10)
mo_hist <- fit_ontram(mo, x_train = x_train, y_train = y_train, history = TRUE,
    x_test = x_valid, y_test = y_valid)
debugonce(eval_batchwise)
out <- eval_batchwise(mo, x_valid, y_valid, NULL, 5, as.numeric(wine$rating))
loss_from_eval(out$preds)
plots_from_eval(out$preds)

LucasKookUZH/ontram-pkg documentation built on March 27, 2023, 6:05 p.m.