Module: TrainTestSplit::Split

Defined in:
lib/train_test_split.rb

Class Method Summary collapse

Class Method Details

.train_test_split(total_data_set, test_size = 0.25) ⇒ Object 



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# File 'lib/train_test_split.rb', line 4

def self.train_test_split(total_data_set, test_size = 0.25)
	if test_size > 1.0
   test_size = 1.0
 elsif test_size < 0
   test_size = 0.0
 end
 test_set_count = (total_data_set.length * test_size).floor
 if test_set_count == 0
   raise StandardError, "Test size resulted in a test set of 0. Increase the test size."
 elsif test_set_count == total_data_set.length
   raise StandardError, "Test size resulted in a training set of 0. Decrease the test size."
 end
#  shuffle data
 total_data_set.shuffle!
 test_set = total_data_set[0..test_set_count]
 training_set = total_data_set[test_set_count+1..total_data_set.length]
#  make train data X and Y
training_set_Y = training_set.map(&:last)
 training_set.map{|row| row.pop}
#  make test data X and Y
test_set_Y = test_set.map(&:last)
 test_set.map{|row| row.pop}
 return training_set, training_set_Y, test_set, test_set_Y
end

.train_validation_test_split(total_data_set, validation_size = 0.15, test_size = 0.10) ⇒ Object 



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# File 'lib/train_test_split.rb', line 29

def self.train_validation_test_split(total_data_set, validation_size = 0.15, test_size = 0.10)
	if test_size > 1.0
   test_size = 1.0
	elsif validation_size > 1.0
   validation_size = 1.0
 elsif validation_size < 0
   validation_size = 0.0
 elsif test_size < 0
   test_size = 0.0
 end
 test_set_count = (total_data_set.length * test_size).floor
 validation_size_count = (total_data_set.length * validation_size).floor
 if test_set_count == 0
   raise StandardError, "Test size resulted in a test set of 0. Increase the test size."
 elsif test_set_count == total_data_set.length
   raise StandardError, "Test size resulted in a training set of 0. Decrease the test size."
 end
 if validation_size_count == 0
   raise StandardError, "validation size resulted in a test set of 0. Increase the validation data size."
 elsif test_set_count == total_data_set.length
   raise StandardError, "validation size resulted in a training set of 0. Decrease the validation data size."
 end
#  shuffle data
 total_data_set.shuffle!
 val_count = test_set_count + validation_size_count
 test_set = total_data_set[0..test_set_count]
 validation_set = total_data_set[test_set_count+1..val_count]
 training_set = total_data_set[val_count+1..total_data_set.length]
#  make train data X and Y
training_set_Y = training_set.map(&:last)
 training_set.map{|row| row.pop}
#  make test data X and Y
test_set_Y = test_set.map(&:last)
 test_set.map{|row| row.pop}
#  make validation data X and Y
validation_set_Y = validation_set.map(&:last)
 validation_set.map{|row| row.pop}
 return training_set, training_set_Y, validation_set, validation_set_Y, test_set, test_set_Y
end