Neural Network based ML

Single Hidden NN, DNN, Stuttgart Neural Network

Single Hidden NN

Input Data

Parameters	Input
*Target Data	Input data
*Model Name	Name of the model (fill out at your discretion)
*Output Name	Name of the output after calculation
Merge Data	If not empty, the prediction data will be stored in the selected data frame(optional)
*X (all data type)	User-selected columns to be X one or more columns should be selected
*Y	User-selected column to be Y Only one column should be selected

[Task Information of Single Hidden NN]

DNN

Input Data

Parameters	Input
*Target Data	Input data
*Model Name	Name of the model (fill out at your discretion)
*Output Name	Name of the output after calculation
Merge Data	If not empty, the prediction data will be stored in the selected data frame(optional)
*X	User-selected columns to be X At least one numeric/complex column should be selected
*Y	User-selected column to be Y Only one column should be selected

[Task Information of DNN]

Stuttgart Neural Network

Multi Layer Perceptron, Elman Network, Jordan Network

Input Data

Parameters	Input
*Target Data	Input data
*Model Name	Name of the model (fill out at your discretion)
*Output Name	Name of the output after calculation
Merge Data	If not empty, the prediction data will be stored in the selected data frame(optional)
*X (all data type)	User-selected columns to be X At least one column should be selected
*Y	User-selected column to be Y Only one column should be selected

[Task Information of Elman Network]

Workflow Example

[Workflow Example of Single Hidden NN]

R Package

Single Hidden NN: https://www.rdocumentation.org/packages/nnet/versions/7.3-14/topics/nnet

DNN: https://www.rdocumentation.org/packages/neuralnet/versions/1.44.2/topics/neuralnet

Multi Layer Perceptron: https://www.rdocumentation.org/packages/RSNNS/versions/0.4-12/topics/mlp

Elman Network: https://rdrr.io/cran/RSNNS/man/elman.html

Jordan Network: https://rdrr.io/cran/RSNNS/man/jordan.html