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This is a list of datasets for machine learning research. It is part of the list of datasets for machine-learning research. These datasets consist primarily of images or videos for tasks such as object detection, facial recognition, and multi-label classification.
This is a list of open clusters located in the Milky Way. An open cluster is an association of up to a few thousand stars that all formed from the same giant molecular cloud . There are over 1,000 known open clusters in the Milky Way galaxy, but the actual total may be up to ten times higher. [ 1 ]
OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis refers to a family of algorithms and tasks rather than one ...
Pages in category "Open clusters" The following 200 pages are in this category, out of approximately 334 total. This list may not reflect recent changes.
The most used such package is mclust, [35] [36] which is used to cluster continuous data and has been downloaded over 8 million times. [37] The poLCA package [38] clusters categorical data using the latent class model. The clustMD package [25] clusters mixed data, including continuous, binary, ordinal and nominal variables.
Cutting after the third row will yield clusters {a} {b c} {d e f}, which is a coarser clustering, with a smaller number but larger clusters. This method builds the hierarchy from the individual elements by progressively merging clusters. In our example, we have six elements {a} {b} {c} {d} {e} and {f}.
In computer science, constrained clustering is a class of semi-supervised learning algorithms. Typically, constrained clustering incorporates either a set of must-link constraints, cannot-link constraints, or both, with a data clustering algorithm. A cluster in which the members conform to all must-link and cannot-link constraints is called a ...