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lares is an R package designed to automate, improve, and accelerate everyday analytics and machine learning tasks. It offers a wide variety of functions grouped in families for:
Tip: See all available functions and documentation here or type
?lares::
in RStudio to explore interactively.
# CRAN VERSION
install.packages("lares")
# DEV VERSION (latest updates)
# If you don't have remotes installed yet, run: install.packages('remotes')
::install_github("laresbernardo/lares")
remotes# For a full installation with recommended dependencies:
::install_github("laresbernardo/lares", dependencies = TRUE) remotes
Windows users: You may need to install RTools to build the dev version.
lares
in
action!lares
h2o_automl()
, plot_model_results()
–
Automated machine learning pipeline with optimal model selection and
visualizations.freqs()
, distr()
, corr_var()
,
corr_cross()
– Instantly summarize, visualize, and uncover
relationships in your data.ohse()
– Efficient and smart one-hot encoding for
categorical variables.cache_*
– Speed up workflows by caching expensive
computations.robyn_*
– Additional functions to support Robyn inputs
and outputs.fb_*
– Interact with Meta’s Marketing APIgpt_*
– Structured prompts builder and interact with
OpenAI’s APIread_encrypted()
, write_encrypted()
–
Interact with encrypted files to keep secrets safe?lares::function_name
in RStudio for detailed help
on any function.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.
Health stats visible at Monitor.