nda (version 0.2.4)

summary.ndrlm: Summary function of Generalized Network-based Dimensionality Reduction and Linear Regression Model (NDRLM)

Description

Print summary of Generalized Network-based Dimensionality Reduction and Linear Regression Model (NDRLM)

Usage

# S3 method for ndrlm
summary(object, digits = getOption("digits"), ...)

Value

Call

Callback function

fval

Objective function for fitting

pareto

in the case of multiple objectives TRUE (default value) provides pareto-optimal solution, while FALSE provides weighted mean of objective functions (see out_weights)

X

A numeric data frame of input variables

Y

A numeric data frame of output variables

NDA

GNDA object, which is the result of model reduction and features selection

fits

List of linear regrassion models

NDA_weight

Weights of input variables (used in ndr)

NDA_min_evalue

Optimized minimal eigenvector centrality value (used in ndr)

NDA_min_communality

Optimized minimal communality value of indicators (used in ndr)

NDA_com_communalities

Optimized minimal common communalities (used in ndr)

NDA_min_R

Optimized minimal square correlation between indicators (used in ndr)

NSGA

Outpot structure of NSGA-II optimization (list), if the optimization value is true (see in mco::nsga2)

fn

Function (regression) name: NDLM

Arguments

object

an object of class 'ndrlm'.

digits

the number of significant digits to use when add.stats = TRUE.

...

additional arguments affecting the summary produced.

Author

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, ndrlm.

Examples

# Example of summary function of NDRLM without optimization of fittings

X<-freeny.x
Y<-freeny.y
NDRLM<-ndrlm(Y,X,optimize=FALSE)
summary(NDRLM)