FSelectorRcpp on CRAN

March 14, 2017

(This article was first published on http://r-addict.com, and kindly contributed to R-bloggers)

FSelectorRcpp – Rcpp (free of Java/Weka) implementation of FSelector entropy-based feature selection algorithms with a sparse matrix support, has finally arrived on CRAN after a year of development. It is also equipped with a parallel backend.

Big thanks to the main architect: Zygmunt Zawadzki, zstat, and our reviewer: Krzysztof Słomczyński.

If something is missing or not clear – please chat with us on our slack?

Get started: Motivation, Installation and Quick Workflow

Provided functionalities

Blog posts history with use cases

Quick Workflow

A simple entropy based feature selection workflow. Information gain is an easy, linear algorithm that computes the entropy of a dependent and explanatory variables, and the conditional entropy of a dependent variable with a respect to each explanatory variable separately. This simple statistic enables to calculate the belief of the distribution of a dependent variable when we only know the distribution of a explanatory variable.

# install.packages(c('magrittr', 'FSelectorRcpp'))
information_gain(               # Calculate the score for each attribute
    formula = Species ~ .,      # that is on the right side of the formula.
    data = iris,                # Attributes must exist in the passed data.
    type  = "infogain",         # Choose the type of a score to be calculated.
    threads = 2                 # Set number of threads in a parallel backend.
  ) %>%                          
  cut_attrs(                    # Then take attributes with the highest rank.
    k = 2                       # For example: 2 attrs with the higehst rank.
  ) %>%                         
  to_formula(                   # Create a new formula object with 
    attrs = .,                  # the most influencial attrs.
    class = "Species"           
  ) %>%
    formula = .,                # Use that formula in any classification algorithm.
    data = iris,                
    family = "binomial"         

Orly cover


The cover photo of this blog posts comes from https://newevolutiondesigns.com/20-fire-art-wallpapers

To leave a comment for the author, please follow the link and comment on their blog: http://r-addict.com.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)