Structural Equation Modeling with Deep Neural Network and Machine Learning

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Documentation for package ‘SEMdeep’ version 1.0.0

• DESCRIPTION file.
• Package NEWS.

Help Pages

classificationReport	Prediction evaluation report of a classification model
crossValidation	Cross-validation of linear SEM, ML or DNN training models
getConnectionWeight	Connection Weight method for neural network variable importance
getGradientWeight	Gradient Weight method for neural network variable importance
getShapleyR2	Compute variable importance using Shapley (R2) values
getSignificanceTest	Test for the significance of neural network inputs
getVariableImportance	Variable importance for Machine Learning models
mapGraph	Map additional variables (nodes) to a graph object
nplot	Create a plot for a neural network model
predict.DNN	SEM-based out-of-sample prediction using layer-wise DNN
predict.ML	SEM-based out-of-sample prediction using node-wise ML
predict.SEM	SEM-based out-of-sample prediction using layer-wise ordering
SEMdnn	Layer-wise SEM train with a Deep Neural Netwok (DNN)
SEMml	Nodewise SEM train using Machine Learning (ML)