core.noscript.text
Learn how team Helping Hands built an app to recommend opioid treatment facility locations during the HHS Opioid Code-a-Thon.
New to Alteryx and ready to help improve the documentation, I'm jumping in with both feet to tackle some of the wildest: the predictive suite.
Why learning new things is hard, plus four fundamental differences between Excel and R
Many if not most supervised-classification problems involve some degree of class imbalance, where at least one class occurs more frequently than the others. The imbalanced-classifi...
Alteryx has a lot of built in functionality, but the ability to leverage custom R code opens up even more possibilities. After reading an answer on the Alteryx Community many month...
Most real-world data-science design patterns combine several models to solve a single business problem. This post surveys the most common and effective techniques for combining mod...
Cross validation (CV) is a difficult topic. There are many ways to do CV, and articles on the subject can be very technical. This blog post is a gentle introduction to CV. Read it...
Understanding fitting algorithms is the final hurdle between you and some juicy data science design patterns. Make the leap!
Nothing is more stylish than a well-fitted induction algorithm.
Have you ever wanted to combine an intense plot-driven board game with Alteryx and R? Now's your chance!
An advanced-analytics model's induction algorithm is its prediction engine. Learn what induction-algorithm features distinguish parametric statistical models and machine-learning m...
Learn why "all models are wrong, but some models are useful."
Citizen data scientist? Learn design patterns that let you use Alteryx to build data-science expertise into your data analyses and analytical models!
Did you want to enchance your already awesome workflow with a cool interactive visualization that you encountered? In this two part series, I am going to show you how, with a littl...
Moving from R to Python? Make sure you know about these packages.
The recent 10.6 Predictive Release includes the introduction of the Prescriptive Category. This blog post will demonstrate different uses/configurations of the 3 simulation tools (...
At the time I'm writing this, we are focused on putting the finishing touches on the 10.6 release (Now available here). Many of the new capabilities that are being introduced with...
Have you mastered the concepts discussed in Demystifying the R-based Tools, Part 1? Are you ready to take the next step on your Predictive Analytics journey? If so, this post is fo...
Diving into the RPy2 packages and using both R and Python in the same workspace.
Have you ever tried to explore those mysterious tools with an R in the lower right-hand corner and been too confused to continue? Or have you not even installed the Predictive, Tim...
We recently released a Microsoft Kit that included a text analytics tool. I wanted to compare the Microsoft sentiment analysis capability to a couple open source algorithms availab...
Does this sound familiar? You just watched a fantastic demonstration for advanced users on regression modeling. You think (who wouldn’t?!) “These tools look amazing…imagine what I...
Want a way to interactively explore the relationships between products based on their attributes? Trying to understand the results of a market basket analysis? Alteryx provides the...
Support Vector Machines (SVM) is a popular supervised learning algorithm. It has been shown to perform well in various settings and is generally considered as one of the best “out...
You’ve blended your data. Cleansed it. Trained your model. Made more models. Tweaked them. Compared them. You’ve picked THE BEST model. It’s perfect. Now what? You need to get the...
ROC curves are a great tool for binary classification. Learn more in this post!
Introduction to plotting and graphics in R (without ggplot2)
Last Friday was a very busy day for several of us at Alteryx in the wake of the announcement that Microsoft and Revolution Analytics had agreed to have Microsoft acquire Revolution...
Running code in parallel is tricky. This post shows how to quickly (and easily) parallelize your R code.