ndl (version 0.2.18)

summary.ndlCrossvalidate: A summary of a crossvalidation of a Naive Discriminatory Reader Model

Description

A summarization method for an object of the class "ndlCrossvalidate".

Usage

# S3 method for ndlCrossvalidate
summary(object, …)
# S3 method for summary.ndlCrossvalidate
print(x, digits = max(3, getOption("digits") - 3), …)

Arguments

object

An object of class "ndlCrossvalidate", resulting from a call to ndlCrossvalidate.

x

An object of class "summary.ndlCrossvalidate", usually resulting from a call to summary.ndlCrossvalidate.

digits

the number of significant digits to use when printing.

…

further arguments passed to or from other methods.

Value

summary.ndlCrossvalidate returns an object of the class "summary.ndlCrossvalidate", a list with the following components:

call

The call matched to fit the "ndlCrossvalidate" object.

formula

The formula specified for the "ndlCrossvalidate" object.

statistics.summary

The means, minima and maxima of a range descriptive statistics for the fit and performance of individual folds; see ndlStatistics.

crosstable.summary

The means of the crosstabulation of observed and predicted outcomes for the held-out test data.

recall.predicted.summary

The means of the recall values for the individual outcomes predicted with the held-out test data.

precision.predicted.summary

The means of the precision values for the individual outcomes predicted with the held-out test data.

statistics.all

All the values for a range descriptive statistics for the fit and performance of individual folds on the held-out test data; see ndlStatistics.

k

The number of folds.

n.total

The sum frequency of all data points in data.

n.train

The sum frequency of data points used for training the individual models (excluding the individual folds).

n.test

The sum frequency of data points in the individual held-out folds used for testing the individual models.

Details

Calculates overall descriptive statistics of the crossvalidation of a fitted Naive Discriminatory Reader model and prints a nice summary of the key results.

References

Arppe, A. and Baayen, R. H. (in prep.)

See Also

ndlCrossvalidate, ndlClassify, ndlStatistics

Examples

# NOT RUN {
## For examples see examples(ndlCrossvalidate).

# }