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dplyr is an R package whose set of functions are designed to enable dataframe (a spreadsheet-like data structure) manipulation in an intuitive, user-friendly way. It is one of the core packages of the popular tidyverse set of packages in the R programming language. [1]
There is also an active R community around the tidyverse. For example, there is the TidyTuesday social data project organised by the Data Science Learning Community (DSLC), [ 16 ] where varied real-world datasets are released each week for the community to participate, share, practice, and make learning to work with data easier. [ 17 ]
Tibbles and Tibble may refer to: Tibbles, a pet cat which is alleged to have wiped out Lyall's wren on Stephens Island in New Zealand tibble, an alternative to a dataframe or datatable in the tidyverse in the R programming language
Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark;
Programming with Big Data in R (pbdR) [1] is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. [ 2 ] [ 3 ] The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical ...
The image of a function f(x 1, x 2, …, x n) is the set of all values of f when the n-tuple (x 1, x 2, …, x n) runs in the whole domain of f.For a continuous (see below for a definition) real-valued function which has a connected domain, the image is either an interval or a single value.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
a labeling (or interpretation) function L: S → 2 AP. Since R is left-total, it is always possible to construct an infinite path through the Kripke structure. A deadlock state can be modeled by a single outgoing edge back to itself. The labeling function L defines for each state s ∈ S the set L(s) of all atomic propositions that are valid in s.