K Nearest Neighbors

Fred Rogers

K Nearest Neighbors (KNN) is a supervised machine learning method that "memorizes" (stores) an entire dataset, then relies on the concepts of proximity and similarity to make predictions about new data. The basic idea is that if a new data point is in some sense "close" to existing data points, its value is likely to be similar to the values of its neighbors. In the Earth Systems Sciences, such techniques can be useful for small- to moderate-scale classification and regression problems.

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NSF Unidata Update: February 2024

In case you missed it — here's a recap of news from the NSF Unidata Program Center for the month of February, 2024.

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NetCDF operators (NCO) version 5.2.1

Version 5.2.1 of the netCDF Operators (NCO) has been released. NCO is an Open Source package that consists of a dozen standalone, command-line programs that take netCDF files as input, then operate (e.g., derive new data, average, print, hyperslab, manipulate metadata) and output the results to screen or files in text, binary, or netCDF formats.

The NCO project is coordinated by Professor Charlie Zender of the Department of Earth System Science, University of California, Irvine. More information about the project, along with binary and source downloads, are available on the SourceForge project page.

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AWIPS Tips: AWIPS 20.3.2-2 Software Release

Welcome back to AWIPS Tips!

We are excited to announce our release of 20.3.2-2 that incorporates many updates and fixes from the 20.3.2-1 release. This release includes installers for CAVE (CentOS7, Windows, VMware Player, and MacOS), and for EDEX (CentOS7).

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AMS 2024 Conference Highlights from the NSF Unidata Staff

AMS 2024 Annual Meeting

This year's annual American Meteorological Society meeting was held 27 January - 1 February 2024 in Baltimore, MD. Several NSF Unidata staff members were able to travel to Baltimore to lead workshops, visit with students, present papers and posters, and otherwise take part in the conference. As always, staff members spent some time meeting with community members at UCAR's exhibit hall booth. The following are some of the conference highlights from the perspective of NSF Unidata staff.

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News and information from the Unidata Program Center
News@Unidata
News and information from the Unidata Program Center

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