set_01:

set_01:

set_02

set_04: This was taken from the TUh EEG Seizure Corpus. There are roughly
        19,000 training vectors, 2,000 development test set vectors,
        and 1174 evaluation set vectors. The vectors are a single
        feature vector taken from the middle of seizure event.

set_05:

set_06:

set_07:

set_08: This set was generated in Spring 2021 using the IMLD application.
        It is 2D data.

set_09: This set was generated for the tuning experiments. The samples for
	each class in the train and dev sets were collected from five tight
	gaussian equispaced around the contour. For eval set, two such
	gaussians were used.

set_10: This set was generated for the tuning experiments to explore
	generalization. The original data for each set was augmented by
	adding gaussian noise. 

set_11: This is a dataset containing patches from TUDP v1.1.1. Each set
	contains equal number of background tissues and Invasive Ductal
	Carcinoma In-Situ (indc) tissues.

set_12: This dataset contains 10-second background and seizure segments
	in numpy data format. The naming convention:
	00000123_s001_t000_label_start_stop.npy

set_13: This is our first set created with IMLD. It is designed to test a
 	simple Gaussian classifier. There are two classes with some
	overlap.
	
set_14: Created in Spring 2022 for ECE 8527. This is a sequential decoding
        task. 1D signals with random events occurring in files.

set_15: Created in Spring 2024 for ECE 8527. This is a subset of the
	TNMG cardiology dataset. It contains 20,000 eval and dev
	files and 200,000 training files. They are all sampled
	at 300 Hz and 2,200 samples long.