Summary: Building a repository of good report components helps you quickly assemble reports that work. Typical things to watch for are: Opening statements, summary sections, key takeaways, useful dimensions and metrics, and recommendations.
Summary: The tm and lsa packages provide you a way of manipulating your text data into a term-document matrix and create new, numeric features. The ngram package lets you find frequent word patterns (e.g. “The cow” is a bi-gram or 2-gram; “The cow said” is a tri-gram or 3-gram). Lastly, for a quick visualization (though […]
I’m on a bit of a reading kick as of late so I wanted to compile a short list of some useful and free data mining / data science books. Most are of a technical nature and come from academia Free Academic Texts on Data Mining An Introduction to Statistical Learning with Applications in R: Covers […]
I’ve had this book on my (digital) shelf for a long time. It’s an intimidating tome. It’s big and broad. However, it’s not exactly what I was expecting. As the book title explains, the main focus is data analysis. Not necessarily statistical or data mining analysis. Instead, chapters one through eleven are focused on plotting, mathematical […]
As I’m working on a Decision Tree tutorial, I picked up the foundational text: Classification and Regression Trees by Breiman, Friedman, Stone, and Olshen. In a nutshell, this book is a math heavy, history lesson on the invention of the decision tree algorithms.