Models.batchLearn: Batch-Learn Regression Models for Process Mining

In thomasWeise/processMineR.models: An R Package for Loading and Processing Models Built with \code{regressoR} and Annotating them with Features

Description

This is a wrapper around regressoR.batchLearn which should provide a shortcut to the recommended modeling techniques.

Usage

Models.batchLearn(q = 0.2, learners = .learners.for.q(q),
  cores = detectCores(), ...)

Arguments

q	the modeling effort to be applied
learners	the model learners to be applied, which has direct implications on the runtime, fitting quality, and models tested
cores	the number of cores to use (>1L leads to parallel execution)
...	Arguments passed on to regressoR::regressoR.batchLearn source the source directory, which is recursively searched for files with data to be modeled destination the destination folder, will be created if not existing loader a loader function which accepts a vector of paths and is supposed to return an n*2 matrix where the first column contains the x values and the second column the y values to model selector a regular expression against which file names are matched. Only matching files are considered. check.directory a function receiving a root folder and the path under root and decides whether this directory path should be recursively investigated (be default always TRUE) learn.single should every single file matching to the selector be modeled separately ? learn.all should all the files in one directory combined and modeled at once? representations a function which can transform a x/y dataset into a set of transformed data instances metricGenerator the learning quality metric generator suffix.single the suffix to append to the files containing the single models suffix.all the suffix to be applied to the files containing the models of all files in a folder includeMetric should the metric used for learning be stored in the files logging should progress information be printed: either TRUE for printing to the console via print, FALSE for no logging, or a path to a file receiving logging information returnResults should we return the computed results or not? skipExisting should already existing models (resulting from a previous, incomplete execution) simply be skipped or overwritting

thomasWeise/processMineR.models documentation built on May 23, 2019, 9:31 a.m.