R: Structural Equation Modeling with Deep Neural Network and Machine Learning Algorithms

# Structural Equation Modeling with Deep Neural Network and Machine Learning Algorithms

## Documentation for package ‘SEMdeep’ version 1.1.1

- DESCRIPTION file
- Package NEWS
- Package README

## 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
getLOCO | Compute variable importance using LOCO values
getShapleyR2 | Compute variable importance using Shapley (R2) values
getSignificanceTest | Test for the significance of neural network input nodes
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 DNN
predict.ML | SEM-based out-of-sample prediction using nodewise ML
predict.SEM | SEM-based out-of-sample prediction using layer-wise ordering
SEMdnn | SEM train with Deep Neural Netwok (DNN) models
SEMml | Nodewise SEM train using Machine Learning (ML)
trainingReport | Training history evaluation of a DNN model