Commit 07d9d81e authored by Marios Kogias's avatar Marios Kogias

[doc] Explain train data size

parent 4241c715
Pipeline #10984 passed with stages
in 9 minutes and 4 seconds
......@@ -390,6 +390,9 @@ thrown.\n\
\n\
In BackProp, training is done in batches. You should set the batch\n\
size properly at class initialization or use setBatchSize().\n\
The number of rows in the input should be in accordance with the\n\
set batch size. If the batch size currently set is incompatible\n\
with the given data an exception is raised.\n\
\n\
.. note::\n\
\n\
......
......@@ -108,7 +108,8 @@ MLPs can be `trained` through backpropagation [2]_, which is a supervised
learning technique. This training procedure requires a set of features with
labels (or targets). Using |project|, this is passed to the `train()` method of
available MLP trainers in two different 2D `NumPy`_ arrays, one for the input
(features) and one for the output (targets).
(features) and one for the output (targets). The number of rows in those two
2D arrays should be equal to the batch size set when creating the model.
.. doctest::
:options: +NORMALIZE_WHITESPACE
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