By: AJDA, Jun 21, 2018
This week we held our first Girls Go Data Mining workshop. The workshop brought together curious women and intuitively introduced them to essential data mining and machine learning concepts. Of course, we used Orange to explore visualizations, build predictive models, perform clustering and dive into text analysis. The workshop was supported by NumFocus through their small development grant initiative and we hope to repeat it next year with even more ladies attending!
By: AJDA, Jan 26, 2018
Scatter plots are great! But sometimes, we need to plot more than two variables to truly understand the data. How can we achieve this, knowing humans can only grasp up to three dimensions? With an optimization of linear projection, of course! Orange recently re-introduced FreeViz, an interactive visualization for plotting multiple variables on a 2-D plane. Let’s load zoo.tab data with File widget and connect FreeViz to it. Zoo data has 16 features describing animals of different types - mammals, amphibians, insects and so on.
By: ASTARIC, Oct 13, 2017
Last week, we presented Orange at the Festival of Open Data, a mini-conference organized by the Slovenian government, dedicated to the promotion of transparent access to government data. In a 10 minute presentation, we showed how Orange can be used to visualize and explore what kinds of vehicles were registered for the first time in Slovenia in 2017. The original dataset is available at theOPSI portal and it consists of 73 files, one for each month since January 2012.
By: AJDA, Sep 22, 2017
Two days ago we held another Introduction to Data Mining workshop at our faculty. This time the target audience was a group of public sector professionals and our challenge was finding the right data set to explain key data mining concepts. Iris is fun, but not everyone is a biologist, right? Fortunately, we found this really nice data set with ballot counts from the Slovenian National Assembly (thanks to Parlameter).
By: AJDA, Aug 8, 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.
By: AJDA, Jun 5, 2017
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.
By: BLAZ, Apr 25, 2017
Say I am given a collection of images of traffic signs, and would like to find which signs stick out. That is, which traffic signs look substantially different from the others. I would assume that the traffic signs are not equally important and that some were designed to be noted before the others. I have assembled a small set of regulatory and warning traffic signs and stored the references to their images in a traffic-signs-w.
By: AJDA, Apr 3, 2017
Data does not always come in a nice tabular form. It can also be a collection of text, audio recordings, video materials or even images. However, computers can only work with numbers, so for any data mining, we need to transform such unstructured data into a vector representation. For retrieving numbers from unstructured data, Orange can use deep network embedders. We have just started to include various embedders in Orange, and for now, they are available for text and images.
By: AJDA, Mar 8, 2017
Thanks to the collaboration with synchrotrons Elettra (Trieste) and Soleil (Paris), Orange is getting an add-on InfraOrange, with widgets for analysis of infrared spectra. Its primary users obviously come from these two institutions, hence we organized the first workshop for InfraOrange at one of them. Some 20 participants spent the first day of the workshop in Trieste learning the basics of Orange and its use for data mining. With Janez at the helm and Marko assisting in the back, we traversed the standard list of visual and statistical techniques and a bit of unsupervised and supervised learning.
By: BLAZ, Dec 22, 2016
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.