From 2bbc1b146cd643ff0dcb3f5eb7ea2bfb1f28301f Mon Sep 17 00:00:00 2001 From: Lewis Van Winkle Date: Tue, 9 Feb 2016 22:09:21 -0600 Subject: [PATCH] Readme work. --- README.md | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 3daad81..04a3861 100644 --- a/README.md +++ b/README.md @@ -79,7 +79,8 @@ Call `genann_free()` when you're finished with an ANN returned by `genann_init() ###Training ANNs ```C -void genann_train(GENANN const *ann, double const *inputs, double const *desired_outputs, double learning_rate); +void genann_train(GENANN const *ann, double const *inputs, + double const *desired_outputs, double learning_rate); ``` `genann_train()` will preform one update using standard backpropogation. It @@ -117,6 +118,12 @@ double const *genann_run(GENANN const *ann, double const *inputs); Call `genann_run()` on a trained ANN to run a feed-forward pass on a given set of inputs. `genann_run()` will provide a pointer to the array of predicted outputs (of `ann->outputs` length). + +##Hints + +- All functions start with `genann_`. +- The code is simple. Dig in and change things. + ##Extra Resources The [comp.ai.neural-nets @@ -128,9 +135,3 @@ I highly recommend the [FANN library](http://leenissen.dk/fann/wp/). Another good library is Peter van Rossum's [Lightweight Neural Network](http://lwneuralnet.sourceforge.net/), which despite its name, is heavier and has more features than GENANN. - -##Hints - -- All functions start with `genann_`. -- The code is simple. Dig in and change things. -