as_LSTM_data_frame: Recreation of a data frame based on preformatted X and Y data...

In stschn/deepANN: Neural Network Toolbox

Recreation of a data frame based on preformatted X and Y data sets

Description

Recreation of a data frame based on preformatted X and Y data sets

Usage

as_LSTM_data_frame(x, y, xnames, ynames, timesteps = 1L, suffix = "_t")

Arguments

x	A feature data set, usually a matrix or data frame, returned by get_LSTM_XY.
y	An outcome data set, usually a vector, matrix or data frame, returned by get_LSTM_XY.
xnames	Names of the features.
ynames	Names of the outcomes.
timesteps	Number of timesteps; stands for the number of different periods within one sample (record) of the result, the resampled feature matrix x.
suffix	The suffix for every feature per timestep or period.

Value

A data frame with outcome column(s) and a further resampled feature matrix. The feature matrix within this data frame has the following forward oriented form: x1(t1), x1(t2), x1(t3)...x2(t1), x2(t2), x2(t3)...x3(t1), x3(t2), x3(t3)...

See Also

get_LSTM_XY.

Other Recurrent Neural Network (RNN): as_LSTM_X(), as_LSTM_Y(), as_LSTM_period_outcome(), as_lag(), as_timesteps(), build_LSTM(), fit_LSTM(), get_LSTM_XY(), get_period_shift(), load_weights_ANN(), predict_ANN(), save_weights_ANN(), start_invert_differencing()

stschn/deepANN documentation built on June 25, 2024, 7:27 a.m.