updated README

NeuraLegion · Dec 17, 2017 · 00f11e7 · 00f11e7
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Showing 2 changed files with 10 additions and 15 deletions.
diff --git a/README.md b/README.md
@@ -21,14 +21,15 @@ dependencies:
 Look at the spec for most functions
 
 ```crystal
-require "crystal-fann"
 ann = Fann::Network::Standard.new(2, [2], 1)
-500.times do
-  ann.train_single([1.0, 0.1], [0.5])
+ann.randomize_weights(0.0, 1.0)
+3000.times do
+  ann.train_single([1.0, 0.0], [0.5])
 end
-result = ann.run([1.0, 0.1])
+result = ann.run([1.0, 0.0])
 # Remember to close the network when done to free allocated C memory
 ann.close
+(result < [0.55] && result > [0.45]).should be_true
 ```
 
 ```crystal
@@ -38,15 +39,13 @@ input = [[0.0, 0.0], [0.0, 1.0], [1.0, 0.0], [1.0, 1.0]]
 output = [[0.0], [1.0], [1.0], [0.0]]
 train_data = Fann::TrainData.new(input, output)
 data = train_data.train_data
-ann.train_algorithm(LibFANN::TrainEnum::TrainRprop)
-ann.set_hidden_layer_activation_func(LibFANN::ActivationfuncEnum::Linear)
-ann.set_output_layer_activation_func(LibFANN::ActivationfuncEnum::Linear)
+ann.randomize_weights(0.0, 1.0)
 if data
-  ann.train_batch(data, {:max_runs => 8000, :desired_mse => 0.001_f64, :log_each => 1000})
+  ann.train_batch(data, {:max_runs => 8000, :desired_mse => 0.001, :log_each => 1000})
 end
 result = ann.run([1.0, 1.0])
 ann.close
-(result < [0.1]).should be_true
+(result < [0.15]).should be_true
 ```
 
 ```crystal
@@ -57,10 +56,9 @@ output = [[0.0], [1.0], [1.0], [0.0]]
 train_data = Fann::TrainData.new(input, output)
 data = train_data.train_data
 ann.train_algorithm(LibFANN::TrainEnum::TrainRprop)
-ann.set_hidden_layer_activation_func(LibFANN::ActivationfuncEnum::Linear)
-ann.set_output_layer_activation_func(LibFANN::ActivationfuncEnum::Linear)
+ann.randomize_weights(0.0, 1.0)
 if data
-  ann.train_batch(data, {:max_neurons => 500, :desired_mse => 0.1_f64, :log_each => 10})
+  ann.train_batch(data, {:max_neurons => 500, :desired_mse => 0.001, :log_each => 10})
 end
 result = ann.run([1.0, 1.0])
 ann.close

diff --git a/spec/network_spec.cr b/spec/network_spec.cr
@@ -49,10 +49,7 @@ describe Fann::Network do
     output = [[0.0], [1.0], [1.0], [0.0]]
     train_data = Fann::TrainData.new(input, output)
     data = train_data.train_data
-    # ann.train_algorithem(LibFANN::TrainEnum::TrainSarprop)
     ann.randomize_weights(0.0, 1.0)
-    # ann.set_hidden_layer_activation_func(LibFANN::ActivationfuncEnum::LeakyRelu)
-    # ann.set_output_layer_activation_func(LibFANN::ActivationfuncEnum::LeakyRelu)
     if data
       ann.train_batch(data, {:max_runs => 8000, :desired_mse => 0.001, :log_each => 1000})
     end