Orange Blog

Author: AJDA, May 3, 2018

Data Mining Course at Higher School of Economics, Moscow

Janez and I have recently returned from a two-week stay in Moscow, Russian Federation, where we were teaching data mining to MA students of Applied Statistics. This is a new Master’s course that attracts the best students from different backgrounds and teaches them statistical methods for work in the industry. It was a real pleasure working at HSE. The students were proactive by asking questions and really challenged us to do our best.


Author: AJDA, Jan 5, 2018

Stack Everything!

We all know that sometimes many is better than few. Therefore we are happy to introduce the Stack widget. It is available in Prototypes add-on for now. Stacking enables you to combine several trained models into one meta model and use it in Test&Score just like any other model. This comes in handy with complex problems, where one classifier might fail, but many could come up with something that works. Let’s see an example.


Author: AJDA, Nov 29, 2017

How to Properly Test Models

On Monday we finished the second part of the workshop for the Statistical Office of Republic of Slovenia. The crowd was tough - these guys knew their numbers and asked many challenging questions. And we loved it! One thing we discussed was how to properly test your model. Ok, we know never to test on the same data you’ve built your model with, but even training and testing on separate data is sometimes not enough.


Author: AJDA, Nov 3, 2017

Neural Network is Back!

We know you’ve missed it. We’ve been getting many requests to bring back Neural Network widget, but we also had many reservations about it. Neural networks are powerful and great, but to do them right is not straight-forward. And to do them right in the context of a GUI-based visual programming tool like Orange is a twisted double helix of a roller coaster. Do we make each layer a widget and then stack them?


Author: BLAZ, Aug 11, 2017

It's Sailing Time (Again)

Every fall I teach a course on Introduction to Data Mining. And while the course is really on statistical learning and its applications, I also venture into classification trees. For several reasons. First, I can introduce information gain and with it feature scoring and ranking. Second, classification trees are one of the first machine learning approaches co-invented by engineers (Ross Quinlan) and statisticians (Leo Breiman, Jerome Friedman, Charles J. Stone, Richard A.

Categories: classification tree

Author: AJDA, Aug 8, 2017

Text Analysis Workshop at Digital Humanities 2017

How do you explain text mining in 3 hours? Is it even possible? Can someone be ready to build predictive models and perform clustering in a single afternoon? It seems so, especially when Orange is involved. Yesterday, on August 7, we held a 3-hour workshop on text mining and text analysis for a large crowd of esteemed researchers at Digital Humanities 2017 in Montreal, Canada. Surely, after 3 hours everyone was exhausted, both the audience and the lecturers.


Author: AJDA, Jun 5, 2017

Nomogram

One more exciting visualization has been introduced to Orange - a Nomogram. In general, nomograms are graphical devices that can approximate the calculation of some function. A Nomogram widget in Orange visualizes Logistic Regression and Naive Bayes classification models, and compute the class probabilities given a set of attributes values. In the nomogram, we can check how changing of the attribute values affect the class probabilities, and since the widget (like widgets in Orange) is interactive, we can do this on the fly.


Author: AJDA, Apr 7, 2017

Model replaces Classify and Regression

Did you recently wonder where did Classification Tree go? Or what happened to Majority? Orange 3.4.0 introduced a new widget category, Model, which now contains all supervised learning algorithms in one place and replaces the separate Classify and Regression categories. This, however, was not a mere cosmetic change to the widget hierarchy. We wanted to simplify the interface for new users and make finding an appropriate learning algorithm easier. Moreover, now you can reuse some workflows on different data sets, say housing.


Author: BLAZ, Dec 22, 2016

The Beauty of Random Forest

It is the time of the year when we adore Christmas trees. But these are not the only trees we, at Orange team, think about. In fact, through almost life-long professional deformation of being a data scientist, when I think about trees I would often think about classification and regression trees. And they can be beautiful as well. Not only for their elegance in explaining the hidden patterns, but aesthetically, when rendered in Orange.


Author: AJDA, Nov 30, 2016

Data Mining for Political Scientists

Being a political scientist, I did not even hear about data mining before I’ve joined Biolab. And naturally, as with all good things, data mining started to grow on me. Give me some data, connect a bunch of widgets and see the magic happen! But hold on! There are still many social scientists out there who haven’t yet heard about the wonderful world of data mining, text mining and machine learning.