Blog Archives

Installing WVPlots and “knitting R markdown”

May 20, 2016
By
Installing WVPlots and “knitting R markdown”

Some readers have been having a bit of trouble using devtools to install WVPlots. I thought I would write a note with a few instructions to help. These are things you should not have to do often, and things those of us already running R have stumbled through and forgotten about. First you will need … Continue reading...

Read more »

For a short time: Half Off Some Manning Data Science Books

May 12, 2016
By

Our publisher Manning Publications is celebrating the release of a new data science in Python title Introducing Data Science by offering it and other Manning titles at half off until Wednesday, May 18. As part of the promotion you can also use the supplied discount code mlcielenlt for half off some R titles including R … Continue reading...

Read more »

Coming up: principal components analysis

May 7, 2016
By
Coming up: principal components analysis

Just a “heads-up.” I’ve been editing a two-part series Nina Zumel is writing on some of the pitfalls of improperly applied principal components analysis/regression and how to avoid them (we are using the plural spelling as used in following Everitt The Cambridge Dictionary of Statistics). The series is looking absolutely fantastic and I think it … Continue reading...

Read more »

vtreat cross frames

May 5, 2016
By
vtreat cross frames

vtreat cross frames John Mount, Nina Zumel 2016-05-05 As a follow on to “On Nested Models” we work R examples demonstrating “cross validated training frames” (or “cross frames”) in vtreat. Consider the following data frame. The outcome only depends on the “good” variables, not on the (high degree of freedom) “bad” variables. Modeling such a … Continue reading...

Read more »

On Nested Models

April 26, 2016
By
On Nested Models

We have been recently working on and presenting on nested modeling issues. These are situations where the output of one trained machine learning model is part of the input of a later model or procedure. I am now of the opinion that correct treatment of nested models is one of the biggest opportunities for improvement … Continue reading...

Read more »

Improved vtreat documentation

April 17, 2016
By
Improved vtreat documentation

Nina Zumel has donated some time to greatly improve the vtreat R package documentation (now available as pre-rendered HTML here). vtreat is an R data.frame processor/conditioner package that helps prepare real-world data for predictive modeling in a statistically justifiable manner. Even with modern machine learning techniques (random forests, support vector machines, neural nets, gradient boosted … Continue reading...

Read more »

Free data science video lecture: debugging in R

April 9, 2016
By

We are pleased to release a new free data science video lecture: Debugging R code using R, RStudio and wrapper functions. In this 8 minute video we demonstrate the incredible power of R using wrapper functions to catch errors for later reproduction and debugging. If you haven’t tried these techniques this will really improve your … Continue reading...

Read more »

Half off Win-Vector data science books and video training!

April 8, 2016
By

We are pleased to announce our book Practical Data Science with R (Nina Zumel, John Mount, Manning 2014) is part of Manning’s “Deal of the Day” of April 9th 2016. This one day only offer gets you half off for physical book (with free e-copy) or paid e-copy (e-copy simultaneous pdf + ePub + kindle, … Continue reading...

Read more »

A bit on the F1 score floor

April 2, 2016
By
A bit on the F1 score floor

At Strata+Hadoop World “R Day” Tutorial, Tuesday, March 29 2016, San Jose, California we spent some time on classifier measures derived from the so-called “confusion matrix.” We repeated our usual admonition to not use “accuracy” as a project goal (business people tend to ask for it as it is the word they are most familiar … Continue reading...

Read more »

WVPlots: example plots in R using ggplot2

April 1, 2016
By
WVPlots: example plots in R using ggplot2

Nina Zumel and I have been working on packaging our favorite graphing techniques in a more reusable way that emphasizes the analysis task at hand over the steps needed to produce a good visualization. The idea is: we sacrifice some of the flexibility and composability inherent to ggplot2 in R for a menu of prescribed … Continue reading...

Read more »

Sponsors

Mango solutions



RStudio homepage



Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training



http://www.eoda.de









ODSC

CRC R books series











Contact us if you wish to help support R-bloggers, and place your banner here.

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)