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helda
View on CRAN: Click
here
Download and install helda package within the R console
Install from CRAN:
install.packages("helda")
Install from Github:
library("remotes")
install_github("cran/helda")
Install by package version:
library("remotes")
install_version("helda", "1.1.5")
Attach the package and use:
library("helda")
Maintained by
Simon Corde
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
First Published: 2020-01-31
Latest Update: 2023-03-01
Description:
The main focus is on preprocessing and data visualization of machine learning models performances.Some functions allow to fill in gaps in time series using linear interpolation on panel data some functionspermit to draw lift effect and lift curve in order to benchmark machine learning models or you can even findthe optimal number of clusters in agglomerative clustering algorithm.
How to cite:
Simon Corde (2020). helda: Preprocess Data and Get Better Insights from Machine Learning
Models. R package version 1.1.5, https://cran.r-project.org/web/packages/helda. Accessed 07 Apr. 2025.
Previous versions and publish date:
Other packages that cited helda R package
View helda citation profile
Other R packages that helda depends,
imports, suggests or enhances
Functions, R codes and Examples using
the helda R package
Some associated functions: cluster_centroid . compute_global_inertia . compute_inertia_ahc . create_calendar . create_formula . gap_to_fill . kmeans_procedure . lift_curve . lift_effect . proc_freq . start_end_to_fill . titanic_testing . titanic_training . titanic_validation . windows_to_linux_path . world_countries_pop .
Some associated R codes: cluster_centroid.R . compute_global_inertia.R . compute_inertia_ahc.R . create_calendar.R . create_formula.R . gap_to_fill.R . kmeans_procedure.R . lift_curve.R . lift_effect.R . proc_freq.R . start_end_to_fill.R . titanic_testing.R . titanic_training.R . titanic_validation.R . windows_to_linux_path.R . world_countries_pop.R . Full helda package functions and examples
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