summary.ndrlm function

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

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

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

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.

Returns

• 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

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>.

Author(s)

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

e-mail*: kosztyan.zsolt@gtk.uni-pannon.hu

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)