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Logistic regression is used in various fields, including machine learning, most medical fields, and social sciences. For example, the Trauma and Injury Severity Score (), which is widely used to predict mortality in injured patients, was originally developed by Boyd et al. using logistic regression. [6]
Univariate is a term commonly used in statistics to describe a type of data which consists of observations on only a single characteristic or attribute. A simple example of univariate data would be the salaries of workers in industry. [1]
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel, distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
Most syntactic treebanks annotate variants of either phrase structure (left) or dependency structure (right).. In linguistics, a treebank is a parsed text corpus that annotates syntactic or semantic sentence structure.
The set of images in the MNIST database was created in 1994 as a combination of two of NIST's databases: Special Database 1; and Special Database 3. [16]Special Database 1 and Special Database 3 consist of digits written by high school students and employees of the United States Census Bureau, respectively.
Knowledge panel data about Thomas Jefferson displayed on Google Search, as of January 2015. The Google Knowledge Graph is a knowledge base from which Google serves relevant information in an infobox beside its search results.
An example of the first resample might look like this X 1 * = x 2, x 1, x 10, x 10, x 3, x 4, x 6, x 7, x 1, x 9. There are some duplicates since a bootstrap resample comes from sampling with replacement from the data. Also the number of data points in a bootstrap resample is equal to the number of data points in our original observations.
Findable. The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services, so this is an essential component of the FAIRification process.