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The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites . The datasets are ported on open data portals .
The data set is approximated by the closest tree with some penalty for the excessive number of nodes, bending and stretching. Then the so-called "metro map" is constructed. [4] The data points are projected into the closest node. For each node the pie diagram of the projected points is prepared. The area of the pie is proportional to the number ...
RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [70] [71] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.
The University of California Irvine hosts the UCI Machine Learning Repository, a data resource which is very popular among machine learning researchers and data mining practitioners. [97] It was created in 1987 and contains 622 datasets from several domains including biology, medicine, physics, engineering, social sciences, games, and others ...
Various plots of the multivariate data set Iris flower data set introduced by Ronald Fisher (1936). [1]A data set (or dataset) is a collection of data.In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the data set in question.
re3data.org is a global registry of research data repositories from all academic disciplines. It provides an overview of existing research data repositories in order to help researchers to identify a suitable repository for their data and thus comply with requirements set out in data policies. [1] [2] The registry went live in autumn 2012. [3]
Caltech 101 is a data set of digital images created in September 2003 and compiled by Fei-Fei Li, Marco Andreetto, Marc 'Aurelio Ranzato and Pietro Perona at the California Institute of Technology. It is intended to facilitate computer vision research and techniques and is most applicable to techniques involving image recognition classification ...
The following tree was constructed using JBoost on the spambase dataset [3] (available from the UCI Machine Learning Repository). [4] In this example, spam is coded as 1 and regular email is coded as −1. An ADTree for 6 iterations on the Spambase dataset. The following table contains part of the information for a single instance.