The Breast Cancer Histopathological Image Classification (BreakHis) is composed of 9,109 microscopic images of breast tumor tissue collected from 82 patients using different magnifying factors (40X, 100X, 200X, and 400X). To date, it contains 2,480 benign and 5,429 malignant samples (700X460 pixels, 3-channel RGB, 8-bit depth in each channel, PNG format).
This dataset consists of high-dimensional data streams collected from a cyber-physical 118-bus power system, offering a valuable resource for fault diagnosis and classification in large-scale smart grids.
This dataset collection contains eleven datasets used in Locally Linear Embedding and fMRI feature selection in psychiatric classification.
The datasets given in the Links section are reduced subsets of those contained in their respective tar files (a consequence of Mendeley Data's 10GB limitation).
The Linked datasets (not the tar files) contain just the MATLAB file and the resting state image (or block-design fMRI for the MRN dataset), where appropriate.
