dnn.weights: Loadings Comparison Test Deep Learning Neural Network Weights
In EGAnet: Exploratory Graph Analysis – a Framework for Estimating the Number of Dimensions in Multivariate Data using Network Psychometrics
dnn.weights R Documentation
Loadings Comparison Test Deep Learning Neural Network Weights
Description
A list of weights from four different neural network models:
random vs. non-random model (r_nr_weights),
low correlation factor vs. network model (lf_n_weights),
high correlation with variables less than or equal to factors vs. network model (hlf_n_weights), and
high correlation with variables greater than factors vs. network model (hgf_n_weights)
Usage
data(dnn.weights)
Format
A list of with a length of 4
Examples
data("dnn.weights")
EGAnet documentation built on Sept. 28, 2024, 9:06 a.m.
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| dnn.weights | R Documentation |
Loadings Comparison Test Deep Learning Neural Network Weights
Description
A list of weights from four different neural network models:
random vs. non-random model (r_nr_weights),
low correlation factor vs. network model (lf_n_weights),
high correlation with variables less than or equal to factors vs. network model (hlf_n_weights), and
high correlation with variables greater than factors vs. network model (hgf_n_weights)
Usage
data(dnn.weights)
Format
A list of with a length of 4
Examples
data("dnn.weights")
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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