train.in and cross.in
contain the training and cross-validation data, respectively.
The first line contains an integer N
with the total number
of entries to be read in. There are two different ways of
interpreting the data, depending on how flag_ts
(the first parameter in data.in)
has been set.
Time series prediction: flag_ts=1
A time series of length N is read in.
Interpolation: flag_ts=0
N must be devideable by
input_grid_size+1,
where input_grid_size is the
size of the input grid,
defined in topo.in.
The first input_grid_size numbers are interpreted as
the input elements (presented at the input layer),
while the following
value is defined as the target variables.
The next input_grid_size entries are again interpreted
as input elements, followed by another target variable.
This scheme is repeated throughout
the whole file.
The cross-validation set is only read in
if flag_cross=1
(where flag_cross is the second element in
data.in).