_src_dataio Directory Reference

Files
	data_accessor.hpp
	Defines interface for data access implementations.
	data_accessor_splitting.hpp
	Defines support for data splitting.
	data_accessor_splitting_mem.hpp
	Implements data access to data cached entirely in memory, concrete file type support is delegated to derived classes.
	data_accessor_splitting_memARFF.hpp
	Implements data access to data cached entirely in memory, read once from ARFF files.
	data_accessor_splitting_memCSV.hpp
	Implements data access to data cached entirely in memory, read once from CSV files.
	data_accessor_splitting_memTRN.hpp
	Implements data access to data cached entirely in memory, read once from TRN files.
	data_accessor_universe.hpp
	Data-free accessor over an abstract feature universe (--features N; pure set-function optimization).
	data_file_ARFF.hpp
	Enables data accessor objects to read ARFF (Weka) type of data files.
	data_file_CSV.hpp
	Enables data accessor objects to read CSV (delimited text, e.g. Excel export) data files.
	data_file_TRN.hpp
	Enables data accessor objects to read TRN type of data files.
	data_intervaller.hpp
	Container to hold a list of Data_Interval; implements nested interval reduction.
	data_scaler.hpp
	Defines interface for data scaling implementations (for use in data accessors).
	data_scaler_to01.hpp
	Implements data normalization (of all feature values) to interval [0,1].
	data_scaler_void.hpp
	Void data scaler, to bypass data normalization.
	data_scaler_white.hpp
	Implements data whitening (as result, each feature mean value is 0 with normalized stddev).
	data_splitter.hpp
	Defines interface for data splitting implementations (for use in data accessors).
	data_splitter_5050.hpp
	Implements train/test data splitting: first 50% of original data for training, second 50% for testing.
	data_splitter_cv.hpp
	Implements train/test data splitting: by means of k-fold cross-validation.
	data_splitter_holdout.hpp
	Implements train/test data splitting: use initial x% of original data for training, the rest for testing.
	data_splitter_leave1out.hpp
	Implements train/test data splitting: by means of leave-one-out.
	data_splitter_randfix.hpp
	Implements train/test data splitting: equal to Data_Splitter_RandomRandom except that the same test data is returned in each loop.
	data_splitter_randrand.hpp
	Implements train/test data splitting: use randomly chosen x% of data samples for training and another y% of data for testing, without overlaps.
	data_splitter_resub.hpp
	Implements train/test data splitting: use all data both for training and then once more for testing.