lib/ruby_brain/network.rb in ruby_brain-0.1.3 vs lib/ruby_brain/network.rb in ruby_brain-0.1.4

@@ -1,10 +1,7 @@
 module RubyBrain
   class Network
-    extend Forwardable
-    def_delegators :@weights_set, :overwrite_weights, :get_weights_as_array
-
     attr_accessor :learning_rate
     
     # Constructor of Network class
     # 
     # @example network structure Array(num_units_list)
@@ -136,10 +133,10 @@
     # @param monitoring_channels [Array<Symbol>] Specify which log should be reported. Now you can select only `:best_params_training`
     def learn(inputs_set, outputs_set, max_training_count=50, tolerance=0.0, monitoring_channels=[])
       raise RubyBrain::Exception::TrainingDataError if inputs_set.size != outputs_set.size
       #      raise "inputs_set and outputs_set has different size!!!!" if inputs_set.size != outputs_set.size
 
-      best_error = 9999999999999
+      best_error = Float::INFINITY
       best_weights_array = []
       max_training_count.times do |i_training|
         accumulated_errors = 0.0 # for rms
         inputs_set.zip(outputs_set).each do |t_input, t_output|
           forward_outputs = get_forward_outputs(t_input)