Introduction In this post, we will learn to work with categorical/qualitative data in R using forcats. Let us begin by installing and loading forcats and a set of other pacakges we will be using. Libraries & Code We will use the following packages: forcats dplyr magrittr ggplot2 tibbe purrr and ...

Building a historical, genre-based corpus Building a Naive Bayes classifier Model assessment & confusion matrix Summary In this short post, we outline a Naive Bayes (NB) approach to genre-based text classification. First, we introduce & describe a corpus derived from Google News’ RSS feed, which includes source and genre information. We then ...

This note is just a quick follow-up to our last note on correcting the bias in estimated standard deviations for binomial experiments. For normal deviates there is, of course, a well know scaling correction that returns an unbiased estimate for observed standard deviations. It (from the same source): … provides an ...

Despite their now inherent evil status, GitHub has some tools other repository aggregators do not. One such tool is the free vulnerability alert service which will scan repositories for outdated+vulnerable dependencies. Now, “R” is nowhere near a first-class citizen in the internet writ large, including software development tooling (e....

by Angelika Stefan & Felix Schönbrodt Almost all researchers have experienced the tingling feeling of suspense that arises right before they take a look at long-awaited data: Will they support their favored hypothesis? Will they yield interesting or even groundbreaking results? In a perfect world (especially one without publication bias), ...

In previous post I wrote about how to set connection with Magento 2 REST API from R and make queries to universal search. Now let’s see how  use filtered search. Also we’ll use other than universal search endpoints that provide access to more specific Magento 2 store information. Using filtered… ...

Dimensionality reduction has two primary use cases: data exploration and machine learning. It is useful for data exploration because dimensionality reduction to few dimensions (e.g. 2 or 3 dimensions) allows for visualizing the samples. Such a visualization can then be used to obtain insights from the data (e.g. detect clusters ...

A few years ago, when I first became aware of Topological Data Analysis (TDA), I was really excited by the possibility that the elegant theorems of Algebraic Topology could provide some new insights into the practical problems of data analysis. But time has passed, and the sober assessment of Larry ...

In the first article of this series, I built an Alpine-based Docker image with R base packages from Alpine’s native repositories, as well as one image with R compiled from source code. The images are hosted on Docker Hub, velaco/alpine-r repository...

Last week at the ODSC West conference, I was thrilled with the interest in my Using AI for Good workshop: it was wonderful to find a room full of data scientists eager to learn how data science and artificial intelligence can be used to help people and the planet. The ...

So you know lapply, sapply, and apply…but…what about rapply, vapply, or eapply? These are generally a little less known as far as the apply family of functions in R go, so this post will explore how they work. rapply Let’s start with rapply. This function has a ...

CategoriesVisualizing Data Tags Data Visualisation ggplot2 R Programming One of the most frustrating issues I face in my professional life is the plentitude of ineffective reports generated within my company. Wherever I look around me is plenty of junk charts, like barplot showing useless 3D effects or ambiguous and crowded ...