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datarobot: 'DataRobot' Predictive Modeling API

For working with the 'DataRobot' predictive modeling platform's API <https://www.datarobot.com/>.

Version: 2.18.6
Depends: R (≥ 3.5), methods, stats
Imports: httr (≥ 1.2.0), jsonlite (≥ 1.0), yaml (≥ 2.1.19)
Suggests: lubridate, knitr, testthat, lintr, data.table, AmesHousing, mlbench, beanplot, doBy, insuranceData, rmarkdown, ggplot2, modelwordcloud, withr, memoise
Published: 2024-03-13
DOI: 10.32614/CRAN.package.datarobot
Author: Ron Pearson [aut], Zachary Deane-Mayer [aut], David Chudzicki [aut], Dallin Akagi [aut], Sergey Yurgenson [aut], Thakur Raj Anand [aut], Peter Hurford [aut], Chester Ismay [aut], AJ Alon [aut], Andrew Watson [aut], Gregory Williams [aut], Anastasiia Tamazlykar [ctb], Mykhailo Poliakov [ctb], DataRobot, Inc. [cph]
Maintainer: AJ Alon <api-maintainer at datarobot.com>
License: MIT + file LICENSE
NeedsCompilation: no
Language: en-US
Materials: NEWS
In views: WebTechnologies
CRAN checks: datarobot results

Documentation:

Reference manual: datarobot.pdf
Vignettes: Advanced Tuning for Models
Advanced Model Insights
Using Calendars
Using Many Models to Compare Datasets
Compliance Documentation
Datetime Partitioning
Introduction to Model Deployment
Introduction to the DataRobot R Package
Introduction to Multiclass
Interpreting Predictive Models Using Partial Dependence Plots
Using Prediction Explanations
Using Rating Tables
Introduction to Time Series
Using Training Predictions
Assessing Variable Importance for Predictive Models of Arbitrary Type

Downloads:

Package source: datarobot_2.18.6.tar.gz
Windows binaries: r-devel: datarobot_2.18.6.zip, r-release: datarobot_2.18.6.zip, r-oldrel: datarobot_2.18.6.zip
macOS binaries: r-release (arm64): datarobot_2.18.6.tgz, r-oldrel (arm64): datarobot_2.18.6.tgz, r-release (x86_64): datarobot_2.18.6.tgz, r-oldrel (x86_64): datarobot_2.18.6.tgz
Old sources: datarobot archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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