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					@ -142,10 +142,15 @@ class Components :
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							#
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							#
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							# We need to make sure that continuous columns are removed 
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							# We need to make sure that continuous columns are removed 
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							if x_cols :
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							if x_cols :
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								_args['data'] = df[list(set(df.columns) - set(x_cols))]
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								_args['data'] = _args['data'][list(set(df.columns) - set(x_cols))]
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							if 'gpu' in args :
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							if 'gpu' in args :
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								_args['gpu'] = self.set_gpu(gpu=args['gpu'])
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								_args['gpu'] = self.set_gpu(gpu=args['gpu'])
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							data.maker.train(**_args)
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							if df.shape[0] and df.shape[0] :
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								#
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								# We have a full blown matrix to be processed 
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								data.maker.train(**_args)
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							else:
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								print ("... skipping training !!")
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							if 'autopilot' in ( list(args.keys())) :
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							if 'autopilot' in ( list(args.keys())) :
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					@ -216,7 +221,7 @@ class Components :
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							_dc = pd.DataFrame()
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							_dc = pd.DataFrame()
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							# for mdf in df :
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							# for mdf in df :
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							args['data'] = df
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							args['data'] = df.copy()
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							#
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							#
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							# The columns that are continuous should also be skipped because they don't need to be synthesied (like-that)
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							# The columns that are continuous should also be skipped because they don't need to be synthesied (like-that)
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							if 'continuous' in args :
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							if 'continuous' in args :
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					@ -232,7 +237,7 @@ class Components :
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							# @TODO: Abstract this !!
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							# @TODO: Abstract this !!
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							#
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							#
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							if x_cols :
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							if x_cols :
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								args['data'] = df[list(set(df.columns) - set(x_cols))]
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								args['data'] = args['data'][list(set(df.columns) - set(x_cols))]
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							args['candidates']	= 1 if 'candidates' not in args else int(args['candidates'])
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							args['candidates']	= 1 if 'candidates' not in args else int(args['candidates'])
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							if 'gpu' in args :
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							if 'gpu' in args :
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