method name change, version update
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@ -11,9 +11,9 @@ this application. While your computer will not burst into flames nor will the su
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likely find more enjoyment of this particular flavour of GP with a little understanding of its intent and design.
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'''
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import csv
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import os
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import sys
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import os
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import csv
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import numpy as np
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import sklearn.metrics as skm
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@ -1420,7 +1420,7 @@ class Base_GP(object):
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pairwise_fitness = self.fx_fitness_train_match(result, solution)
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# elif self.kernel == '[other]': # [OTHER] kernel
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# pairwise_fitness = self.fx_fitness_function_[other](result ?, solution ?)
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# pairwise_fitness = self.fx_fitness_train_[other](result ?, solution ?)
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else: raise Exception('Kernel type is wrong or missing. You entered {}'.format(self.kernel))
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@ -1567,7 +1567,7 @@ class Base_GP(object):
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return tf.cast(tf.equal(solution, result), tf.int32)
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# def fx_fitness_function_[other](self, result, solution): # [OTHER] kernel
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# def fx_fitness_train_[other](self, result, solution): # [OTHER] kernel
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# '''
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# Creates element-wise fitness computation TensorFlow (TF) sub-graph for [other] kernel.
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@ -2,7 +2,7 @@
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# Use Genetic Programming for Classification and Symbolic Regression
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# by Kai Staats, MSc; see LICENSE.md
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# Thanks to Emmanuel Dufourq and Arun Kumar for support during 2014-15 devel; TensorFlow support provided by Iurii Milovanov
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# version 1.0.1
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# version 1.0
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'''
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A word to the newbie, expert, and brave--
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@ -143,7 +143,7 @@ else: # if any other kernel is selected
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menu = ['i','g','m','s','db','']
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while True:
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try:
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gp.display = raw_input('\t Display (i)nteractive, (g)eneration, (m)iminal, or (s)ilent (default m): ')
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gp.display = raw_input('\t Display (i)nteractive, (g)eneration, (m)iminal, (s)ilent, or (d)e(b)ug (default m): ')
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if gp.display not in menu: raise ValueError()
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gp.display = gp.display or 'm'; break
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except ValueError: print '\t\033[32m Select from the options given. Try again ...\n\033[0;0m'
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@ -2,7 +2,7 @@
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# Use Genetic Programming for Classification and Symbolic Regression
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# by Kai Staats, MSc; see LICENSE.md
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# Thanks to Emmanuel Dufourq and Arun Kumar for support during 2014-15 devel; TensorFlow support provided by Iurii Milovanov
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# version 1.0.1
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# version 1.0
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'''
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A word to the newbie, expert, and brave--
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