wrapr 2.0.0 is now up on CRAN.
This means the := variant of unpack[] is now easy to install.
Please give it a try!
Category: Administrativia
Re-Share: vtreat Data Preparation Documentation and Video
I would like to re-share vtreat (R version, Python version) a data preparation documentation for machine learning tasks.
vtreat is a system for preparing messy real world data for predictive modeling tasks (classification, regression, and so on). In particular it is very good at re-coding high-cardinality string-valued (or categorical) variables for later use.
Continue reading Re-Share: vtreat Data Preparation Documentation and Video
Free Coupon for our R Video Course: Introduction to Data Science
For all our remote learners, we are sharing a free coupon code for our R video course Introduction to Data Science. The code is ITDS2020, and can be used at this URL https://www.udemy.com/course/introduction-to-data-science/?couponCode=ITDS2020 . Please check it out and share it!
A Little Something From Practical Data Science with R Chapter 1
Here is a small quote from Practical Data Science with R Chapter 1.
It is often too much to ask for the data scientist to become a domain expert. However, in all cases the data scientist must develop strong domain empathy to help define and solve the right problems.
Interested? Please check it out.
Keep Calm and Use vtreat (in R and in Python)
A big thank you to Dmytro Perepolkin for sharing a “Keep Calm and Use vtreat” poster!
Also, we have translated the Python vtreat steps from our recent “Cross-Methods are a Leak/Variance Trade-Off” article into R vtreat steps here.
This R-port demonstrates the new to R fit/prepare notation!
We want vtreat to be a platform agnostic (works in R, works in Python, works elsewhere) well documented standard methodology.
To this end: Nina and I have re-organized the basic vtreat use documentation as follows:
- Regression:
Rregression example, fit/prepare
interface,
Rregression example, design/prepare/experiment
interface,
Pythonregression
example. - Classification:
Rclassification example, fit/prepare
interface,
Rclassification example, design/prepare/experiment
interface,
Pythonclassification
example. - Unsupervised tasks:
Runsupervised example, fit/prepare
interface,
Runsupervised example, design/prepare/experiment
interface,
Pythonunsupervised
example. - Multinomial classification:
Rmultinomial classification
example, fit/prepare
interface,
Rmultinomial classification example, design/prepare/experiment
interface,
Pythonmultinomial classification
example.
What is New For vtreat 1.5.2?
vtreat version 1.5.2 just became available from CRAN.
We have a logged a few improvement in the NEWS. The changes are small and incremental, as the package is already in a great stable state for production use.
New Data Scientist Stickers
We have a new data scientist sticker!
If you see Nina or John at a conference/MeetUp, please ask us for a sticker!
wrapr Update: Removing Some Under-Used Functions and Classes
For the next version of the R package wrapr we are going to be removing a number of under-used functions/methods and classes. This update will likely happen in March 2020, and is the start of the wrapr 2.* series.
Most of the items being removed are different abstractions for helping with function composition. We ended up moving most of our work to category-theory based composition, so don’t think these various frameworks are needed any longer. If you have been using these items in your own projects, please reach out and we try and find a way to help you out.
Continue reading wrapr Update: Removing Some Under-Used Functions and Classes
wrapr 1.9.6 is now up on CRAN
wrapr 1.9.6 is now up on CRAN.
We unfortunately usually forget to say this. A big thank you to the staff and volunteers at CRAN.
Off topic: Horror Translations by Nina Zumel
In an off-topic post we would like to share a series of horror narrations based on Win Vector LLC’s very own Nina Zumel’s translations of Uruguayan author Horacio Quiroga. This is a free series produced by Rue Morgue
The first is: “The Feather Pillow.” DO NOT LISTEN TO THIS IN BED!
(YouTube link, Rue Morge link, Ephemera link)
More of Nina’s literary work can be found at: Ephemera Experiments in Writing, and Multo (Ghost).