summary.nda: Summary function of Generalized Network-based Dimensionality...

In nda: Generalized Network-Based Dimensionality Reduction and Analysis

Summary function of Generalized Network-based Dimensionality Reduction and Analysis (GNDA)

Description

Print summary of Generalized Network-based Dimensionality Reduction and Analysis (GNDA)

Usage

## S3 method for class 'nda'
summary(object, digits = getOption("digits"), ...)

Arguments

object	an object of class 'nda'.
digits	the number of significant digits to use when add.stats = TRUE.
...	additional arguments affecting the summary produced.

Value

communality	Communality estimates for each item. These are merely the sum of squared factor loadings for that item. It can be interpreted in correlation matrices.
loadings	A standard loading matrix of class “loadings".
uniqueness	Uniqueness values of indicators.
factors	Number of found factors.
scores	Estimates of the factor scores are reported (if covar=FALSE).
n.obs	Number of observations specified or found.

Author(s)

Zsolt T. Kosztyan*, Marcell T. Kurbucz, Attila I. Katona

e-mail*: [e-mail]

References

Kosztyán, Z. T., Katona, A. I., Kurbucz, M. T., & Lantos, Z. (2024). Generalized network-based dimensionality analysis. Expert Systems with Applications, 238, 121779. <URL: https://doi.org/10.1016/j.eswa.2023.121779>.

See Also

biplot, plot, print, ndr.

Examples

# Example of summary function of NDA without feature selection

data("CrimesUSA1990.X")
df<-CrimesUSA1990.X
p<-ndr(df)
summary(p)

# Example of summary function of NDA with feature selection
# minimal eigen values (min_evalue) is 0.0065
# minimal communality value (min_communality) is 0.1
# minimal common communality value (com_communalities) is 0.1

p<-ndr(df,min_evalue = 0.0065,min_communality = 0.1,com_communalities = 0.1)
summary(p)

nda documentation built on Oct. 14, 2024, 5:10 p.m.