Contiene datos sobre pacientes susceptibles de tener diabetes. El campo diabetes contiene la información del diagnóstico. El fichero original disponible en UCI ha sido modificado y extendido con datos ficticios con fines educacionales.
The aim is to distinguish between the presence and absence of cardiac arrhythmia and to classify it in one of the 16 groups:
Class 01 refers to 'normal' ECG
Classes 02 to 15 refers to different classes of arrhythmia
Class 16 refers to the rest of unclassified ones.
For the time being, there exists a computer program that makes such a classification. However there are differences between the cardiolog's and the programs classification. Taking the cardiolog's as a gold standard we aim to minimise this difference by means of machine learning tools.
Diagnostic with 30 features related to Breast Cancer in Wisconsin. The features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image.
This is one of three domains provided by the Oncology Institute that has repeatedly appeared in the machine learning literature. (See also lymphography and primary-tumor.)
This data set includes 201 instances of one class and 85 instances of another class. The instances are described by 9 attributes, some of which are linear and some are nominal.
Data collected from car crashes in the USA in 2011 relating information about location of the crash, road, weather and driver condition
and the severity of any injuries.
This dataset contains data about COVID19 patients. The original source can be found at https://www.kaggle.com/paultimothymooney/does-latitude-impact-the-spread-of-covid-19/dataDisclaimer: The information in the dataset has been filtered and transformed, so it should only be used for demonstration purposes. For investigation uses, please refer to the original source.
