Module Network
source code
Contains the class _Network_ which is used to represent neural nets
**Network Architecture:**
A tacit assumption in all of this stuff is that we're dealing with
feedforward networks.
The network itself is stored as a list of _NetNode_ objects. The list
is ordered in the sense that nodes in earlier/later layers than a
given node are guaranteed to come before/after that node in the list.
This way we can easily generate the values of each node by moving
sequentially through the list, we're guaranteed that every input for a
node has already been filled in.
Each node stores a list (_inputNodes_) of indices of its inputs in the
main node list.
|
__package__ = ' rdkit.ML.Neural '
|
Imports:
numpy,
random,
xrange,
NetNode,
ActFuncs