fdm2id (version 0.9.1)

evaluate: Evaluate several classication (or regression) methods

Description

Evaluation a classification or regression method using bootstrap approach.

Usage

evaluate(
  methods,
  dataset,
  target = NULL,
  size = round(0.7 * nrow(dataset)),
  names = NULL,
  eval = "accuracy",
  seed = NULL,
  ...
)

Arguments

methods

The classification or regression method to be evaluated.

dataset

The dataset to be split (data.frame or matrix).

target

The column index of the target variable (class label or response variable).

size

The size of the training set (as an integer value).

names

Method names.

eval

The evaluation function.

seed

A specified seed for random number generation.

...

Other specific parameters for the leaning method.

Value

The evaluation of the predictions (numeric value).

See Also

bootstrap, evaluation, splitdata

Examples

# NOT RUN {
require ("datasets")
data (iris)
evaluate (c (NB, LDA), iris, target = 5, eval = c ("accuracy", "kappa"), seed = 0)
# }