Answering 59 scikit-learn questions (video)
Watch me answer 59 of YOUR scikit-learn questions in 90 minutes! Topic include class imbalance, preprocessing, categorical features, data leakage, and more…continue reading.
Watch me answer 59 of YOUR scikit-learn questions in 90 minutes! Topic include class imbalance, preprocessing, categorical features, data leakage, and more…continue reading.
Almost a year is now gone since I posted my last update about my shiny-powered search app. It allows to search among currently more than 5000 economic articles that have...continue reading.
This talk was presented virtually at eRum 2020 and useR 2020 by Appsilon engineer Marcin Dubel. Here is a direct link to the video. Be Proud of Your Code! In...continue reading.
We often want to operate only on a specific subset of rows of a data frame. The dplyr filter() function provides a flexible way to extract the rows of interest...continue reading.
Continuous integration is an amazing tool when developing R packages. We push a change to the server, and a process is spawned that checks we haven’t done something silly. It...continue reading.
We’re very chuffed to announce the release of recipes 0.1.13. recipes is an alternative method for creating and preprocessing design matrices that can be used for modeling or visualization. You...continue reading.
This talk was presented virtually at eRum 2020 and useR 2020. Learn more about Appsilon‘s ML wildlife preservation project here. Yes, R programmers can make machine learning models, too! In...continue reading.
Researchers are often interested in comparing statistical network models across groups. For example, Fritz and colleagues compared the relations between resilience factors in a network model for adolescents who did...continue reading.
This article is originally published at https://lcolladotor.github.io/ Thanks for visiting r-craft.org This article is originally published at https://lcolladotor.github.io/ Please visit source website for post related comments.continue reading.
One hundred eighty-four new packages stuck to CRAN in May. The following are my “Top 40” picks in eleven categories: Data, Finance, Genomics, Marketing, Machine Learning, Medicine, Science, Statistics, Time...continue reading.
Photo by Zoltan Tasi on Unsplash In a recent series of blog posts, we introduced the idea of Serious Data Science to help tackle the challenges of effectively implementing data...continue reading.
Photo by Zoltan Tasi on Unsplash In a recent series of blog posts, we introduced the idea of Serious Data Science to help tackle the challenges of effectively implementing data...continue reading.
R package gower was accepted on CRAN on 23 june 2020. This release fixes an edge case, affecting cases with a small number of records and a large number of...continue reading.
June 25th (8:00pm UTC+2) is a date for next Webinar at Why R? Foundation. This time we will have a chance to host Dr. Leon Eyrich Jessen who will present...continue reading.
Hi all, This post is about a way of sampling from a Categorical distribution, which appears in Arthur Dempter‘s approach to inference as a generalization of Bayesian inference (see Figure...continue reading.
In nonlinear dynamics, when the state space is thought to be multidimensional but all we have for data is just a univariate time series, one may attempt to reconstruct the...continue reading.
This article is originally published at https://lcolladotor.github.io/ Thanks for visiting r-craft.org This article is originally published at https://lcolladotor.github.io/ Please visit source website for post related comments.continue reading.
R packages on CRAN needs to pass a series of technical checks. These checks can also be invoked by any user when running R CMD check on the package tar.gz...continue reading.
Hello and welcome to this new issue! Release Date: 2020-06-22 This week’s release was curated by Miles McBain, with help from the RWeekly team members and contributors. How to have...continue reading.
To select only a specific set of interesting data frame columns dplyr offers the select() function to extract columns by names, indices and ranges. You can even rename extracted columns...continue reading.