R/rtemis-package.R

In rtemis: Schema-Driven Machine Learning and Visualization

# rtemis-package.R
# ::rtemis::
# 2015- EDG rtemis.org

#' \pkg{rtemis}: Advanced Machine Learning and Visualization
#'
#' @description
#' Schema-driven machine learning for validated, observable, auditable, and reproducible
#' machine learning workflows.
#'
#' @section Online Documentation and Vignettes:
#' <https://docs.rtemis.org/r/ml>
#'
#' @section Visualization:
#' Model plots (`plot_true_pred()`, `plot_roc()`, `plot_varimp()`, `plot_metric()`,
#' `plot_learning()`, `plot_session()`, `plot_manhattan()`) and `present()` render
#' interactive charts through 'rtemis.draw', which also provides the `draw_*()` functions for
#' data. `draw_linad()` draws a LINAD tree.
#'
#' @section Supervised Learning:
#' By convention, the last column of the data is the outcome variable, and all other columns are
#' predictors. Convenience function [set_outcome] can be used to move a specified column to the
#' end of the data.
#' Regression and Classification is performed using `train()`.
#' This function allows you to preprocess, train, tune, and test models on multiple resamples.
#' Use [available_supervised] to get a list of available algorithms
#'
#' @section Classification:
#' For training of binary classification models, the outcome should be provided as a factor,
#' with the *second* level of the factor being the 'positive' class.
#'
#' @section Clustering:
#' Clustering is performed using `cluster()`.
#' Use [available_clustering] to get a list of available algorithms.
#'
#' @section Decomposition:
#' Decomposition is performed using `decomp()`.
#' Use [available_decomposition] to get a list of available algorithms.
#'
#' @section Type Documentation:
#' Function documentation includes input type (e.g. "Character", "Integer",
#' "Float"/"Numeric", etc).
#' When applicable, value ranges are provided in interval notation. For example, Float: [0, 1)
#' means floats between 0 and 1 including 0, but excluding 1.
#' Categorical variables may include set of allowed values using curly braces.
#' For example, Character: \{"future", "mirai", "none"\}.
#'
#' @section Tabular Data:
#' \pkg{rtemis} internally uses methods for efficient handling of tabular data, with support for
#' `data.frame`, `data.table`, and `tibble`. If a function is documented as accepting
#' "tabular data", it should work with any of these data structures. If a function is documented
#' as accepting only one of these, then it should only be used with that structure.
#' For example, some optimized `data.table` operations that perform in-place modifications only
#' work with `data.table` objects.
#'
#' @section Error Conditions:
#' Errors are signalled as classed conditions that can be handled with
#' [tryCatch()]. See [rtemis_conditions] for the class hierarchy.
#'
#' @name rtemis-package
#' @import stats methods graphics S7 data.table rtemis.core
# rtemis.core exports `gray()` (colored text); exclude grDevices::gray() to
# avoid masking it, matching the previous local definition. Use
# `grDevices::gray()` explicitly where the grayscale palette is needed.
#' @importFrom utils tail
#' @rawNamespace import(grDevices, except = gray)
"_PACKAGE"

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