# Datasets and Functions to Benchmark Neural Network Packages

## Documentation for package ‘NNbenchmark’ version 3.2.0

- DESCRIPTION file.
- Package NEWS.

## Help Pages

NNbenchmark-package | Package NNbenchmark
add2csv | Create or Append a data.frame to a csv File
bWoodN1 | Dataset bWoodN1
cc | Concatenates List and Vectors into a List
clearNN | Detach the Loaded Packages and the ZZ object
createTimer | Create a timer object. Get the data frame of a timer object
detachNN | Detach the Loaded Packages and the ZZ object
funMAE | Calculate the RMSE, MSE, MAE, and WAE Rounded to 4 digits
funMSE | Calculate the RMSE, MSE, MAE, and WAE Rounded to 4 digits
funRMSE | Calculate the RMSE, MSE, MAE, and WAE Rounded to 4 digits
funWAE | Calculate the RMSE, MSE, MAE, and WAE Rounded to 4 digits
getTimer | Create a timer object. Get the data frame of a timer object
ht | Concatenates head() and tail() in vector, list, matrix, data.frame, array
ht9 | Concatenates head() and tail() in vector, list, matrix, data.frame, array
lipoNN | Create a Plot, Add Lines or Points Depending The Context
mDette | Dataset mDette
mFriedman | Dataset mFriedman
mIshigami | Dataset mIshigami
mRef153 | Dataset mRef153
NNbenchmark | Package NNbenchmark
NNbigdatasets | Big Datasets in One list (2020)
NNdatasets | All Datasets in One List
NNdataSummary | A Summary (in data.frame format) of NNdatasets
NNsummary | Summarize Calculations of RMSE, MSE, MAE, and WAE
NNtrainPredict | Generic Functions for Training and Predicting
plotNN | Create a Plot, Add Lines or Points Depending The Context
prepareZZ | Prepare a Dataset For All Possible Formats
timediff | Collect the difftime between two events
timeR | A R6 Class to represent a timer.
timestart | Collect the difftime between two events
trainPredict_1data | Generic Functions for Training and Predicting
trainPredict_1mth1data | Generic Functions for Training and Predicting
trainPredict_1pkg | Generic Functions for Training and Predicting
uDmod1 | Dataset uDmod1
uDmod2 | Dataset uDmod2
uDreyfus1 | Dataset uDreyfus1
uDreyfus2 | Dataset uDreyfus2
uGauss1 | Dataset uGauss1
uGauss2 | Dataset uGauss2
uGauss3 | Dataset uGauss3
uNeuroOne | Dataset uNeuroOne