Today, second post of our series on classification from scratch, following the brief introduction on the logistic regression. Piecewise linear splines To illustrate what’s going on, let us start with a “simple” regression (with only one explanatory variable). The underlying idea is natura non facit saltus, for “nature does not make jumps”, i.e. process governing equations for natural things are continuous. That seems to be a rather strong assumption, because…
Before my course on « big data and economics » at the university of Barcelona in July, I wanted to upload a series of posts on classification techniques, to get an insight on machine learning tools. According to some common idea, machine learning algorithms are black boxes. I wanted to get back on that saying. First of all, isn’t it the case also for regression models, like generalized additive models (with splines)…
Note: Word Press messes up the code. Find the code here: https://github.com/trinker/RandomCaseEffect This past week I was preparing slides for a reading assessment class with a lecture focus on the Visual Word Form Area [VWFA] (Cohen, et al., 2000). This … Continue reading →
This is a quick script showing how to make multi-tabbed .xlsx files. I recently had the need to do this and used the flexible openxlsx package maintained by : Alexander Walker. The package is described by the author like this: … Continue reading →
Lately I’ve been thinking a lot about the connection between prediction models and the decisions that they influence. There is a lot of theory around this, but communicating how the various pieces all fit together with the folks who will use and be impacted by these decisions can be challenging. One of the important conceptual pieces […]
The R language is closely tied to statistics. It’s ancestor was named S, because it was a language for Statistics. The open source descendant could have been named ‘T’, but its creators chose to call it’R.’ Most people learn R as they learn statistics: Here’s a statistical concept, and here’s how you can compute it in R. […]
I’ve had this book on pre-order since spring and it finally arrived on Friday. I subsequently devoured it over the weekend. The book lays out a clear and compelling case for how data-driven algorithms can become — in contrast to their promise of amoral objectivism — efficient means for reproducing and even exacerbating social inequalities […]
Another great turnout at the DataPhilly meetup last night. Was great to see all you random data nerds! Code snippets to generate animated examples here.
The next DataPhilly meetup will feature a medley of machine-learning talks, including an Intro to ML from yours truly. Check out the speakers list and be sure to RSVP. Hope to see you there! Thursday, February 18, 2016 6:00 PM to 9:00 PM Speakers: Corey Chivers Randy Olson Austin Rochford Corey Chivers (Penn Medicine) Abstract: […]
