Orange Blog
By: SALVACARRION, Aug 19, 2016
Making recommendations
This is a guest blog from the Google Summer of Code project. Recommender systems are everywhere, we can find them on YouTube, Amazon, Netflix, iTunes,… This is because they are crucial component in a competitive retail services. How can I know what you may like if I have almost no information about you? The answer: taking Collaborative filtering (CF) approaches. Basically, this means to combine all the little knowledge we have about users and/or items in order to build a grid of knowledge with which we make recommendation.
By: PRIMOZGODEC, Aug 16, 2016
Visualization of Classification Probabilities
This is a guest blog from the Google Summer of Code project. Polynomial Classification widget is implemented as a part of my Google Summer of Code project along with other widgets in educational add-on (see my previous blog). It visualizes probabilities for two-class classification (target vs. rest) using color gradient and contour lines, and it can do so for any Orange learner. Here is an example workflow. The data comes from the File widget.
By: PRIMOZGODEC, Aug 12, 2016
Interactive k-Means
This is a guest blog from the Google Summer of Code project. As a part of my Google Summer of Code project I started developing educational widgets and assemble them in an Educational Add-On for Orange. Educational widgets can be used by students to understand how some key data mining algorithms work and by teachers to demonstrate the working of these algorithms. Here I describe an educational widget for interactive k-means clustering, an algorithm that splits the data into clusters by finding cluster centroids such that the distance between data points and their corresponding centroid is minimized.
By: AJDA, Jul 18, 2016
Network Analysis with Orange
Visualizing relations between data instances can tell us a lot about our data. Let’s see how this works in Orange. We have a data set on machine learning and data mining conferences and journals, with the number of shared authors for each publication venue reported. We can estimate similarity between two conferences using the author profile of a conference: two conference would be similar if they attract the same authors. The data set is already 9 years old, but obviously, it’s about the principle.
By: AJDA, Jul 5, 2016
Rehaul of Text Mining Add-On
Google Summer of Code is progressing nicely and some major improvements are already live! Our students have been working hard and today we’re thanking Alexey for his work on Text Mining add-on. Two major tasks before the midterms were to introduce Twitter widget and rehaul Preprocess Text. Twitter widget was designed to be a part of our summer school program and it worked beautifully. We’ve introduced youngsters to the world of data mining through social networks and one of the most exciting things was to see whether we can predict the author from the tweet content.
By: AJDA, Apr 25, 2016
Association Rules in Orange
Orange is welcoming back one of its more exciting add-ons: Associate! Association rules can help the user quickly and simply discover the underlying relationships and connections between data instances. Yeah! The add-on currently has two widgets: one for Association Rules and the other for Frequent Itemsets. With Frequent Itemsets we first check frequency of items and itemsets in our transaction matrix. This tell us which items (products) and itemsets are the most frequent in our data, so it would make a lot of sense focusing on these products.
By: AJDA, Sep 11, 2015
Hubbing with the Hub widget
So you have painted two data sets and loaded another one from a file, and now you are testing predictions of logistic regression, classification trees and SVM on it? Tired of having to reconnect the Paint data widget and the File widget back and forth whenever you switch between them? Say no more! Look no further! Here is the new Hub widget! Hub widget is the most versatile widget available so far.
By: AJDA, Jul 31, 2015
Datasets in Orange Bioinformatics Add-On
As you might know, Orange comes with several basic widget sets pre-installed. These allow you to upload and explore the data, visualize them, learn from them and make predictions. However, there are also some exciting add-ons available for installation. One of these is a bioinformatics add-on, which is our specialty. Bioinformatics widget set allows you to pursue complex analysis of gene expression by providing access to several external libraries. There are four widgets intended specifically for this - dictyExpress, GEO Data Sets, PIPAx and GenExpress.
By: AJDA, Jun 19, 2015
Orange workshops around the world
Even though the summer is nigh, we are hardly going to catch a summer break this year. Orange team is busy holding workshops around the world to present the latest widgets and data mining tools to the public. Last week we had a very successful tutorial at [BC]2 in Basel, Switzerland, where Marinka and Blaž presented data fusion. A part of the tutorial was a hands-on workshop with Orange’s new add-on for data fusion.
By: AJDA, Jun 5, 2015
Data Fusion Add-on for Orange
Orange is about to get even more exciting! We have created a prototype add-on for data fusion, which will certainly be of interest to many users. Data fusion brings large heterogeneous data sets together to create sensible clusters of related data instances and provides a platform for predictive modelling and recommendation systems. This widget set can be used either to recommend you the next movie to watch based on your demographic characteristics, movies you gave high scores to, your preferred genre, etc.