Orange Blog
By: AJDA, Oct 16, 2015
Learners in Python
We’ve already written about classifying instances in Python. However, it’s always nice to have a comprehensive list of classifiers and a step-by-step procedure at hand. TRAINING THE CLASSIFIER We start with simply importing Orange module into Python and loading our data set. >>>> import Orange >>>> data = Orange.data.Table("titanic") We are using ’titanic.tab’ data. You can load any data set you want, but it does have to have a categorical class variable (for numeric targets use regression).
By: AJDA, Oct 2, 2015
A visit from the Tilburg University
Biolab is currently hosting two amazing data scientists from the Tilburg University - dr. Marie Nilsen and dr. Eric Postma, who are preparing a 20-lecture MOOC on data science for non-technical audience. A part of the course will use Orange. The majority of their students is coming from humanities, law, economy and behavioral studies, thus we are discussing options and opportunities for adapting Orange for social scientists. Another great thing is that the course is designed for beginner level data miners, showcasing that anybody can mine the data and learn from it.
By: AJDA, Aug 14, 2015
Classifying instances with Orange in Python
Last week we showed you how to create your own data table in Python shell. Now we’re going to take you a step further and show you how to easily classify data with Orange. First we’re going to create a new data table with 10 fruits as our instances. import Orange from Orange.data import * color = DiscreteVariable("color", values=["orange", "green", "yellow"])calories = ContinuousVariable("calories") fiber = ContinuousVariable("fiber") fruit = DiscreteVariable("fruit", values=["orange", "apple", "peach"]) domain = Domain([color, calories, fiber], class_vars=fruit) data=Table(domain, [</span> ["green", 4, 1.
By: AJDA, Aug 7, 2015
Creating a new data table in Orange through Python
IMPORT DATA One of the first tasks in Orange data analysis is of course loading your data. If you are using Orange through Python, this is as easy as riding a bike: import Orange data = Orange.data.Table(“iris”) print (data) This will return a neat data table of the famous Iris data set in the console. CREATE YOUR OWN DATA TABLE What if you want to create your own data table from scratch?
By: AJDA, Jul 10, 2015
Learn with Paint Data
Paint Data widget might initially look like a kids’ game, but in combination with other Orange widgets it becomes a very simple and useful tool for conveying statistical concepts, such as k-means, hierarchical clustering and prediction models (like SVM, logistical regression, etc.). The widget enables you to draw your data on a 2-D plane. You can name the x and y axes, select the number of classes (which are represented by different colors) and then position the points on a graph.
By: BLAZ, Jan 6, 2013
New scripting tutorial
Orange just got a new, completely rewritten scripting tutorial. The tutorial uses Orange class hierarchy as introduced for version 2.5. The tutorial is supposed to be a gentle introduction in Orange scripting. It includes many examples, from really simple ones to those more complex. To give you a hint about the later, here is the code for learner with feature subset selection from: class SmallLearner(Orange.classification.PyLearner): def __init__(self, base_learner=Orange.classification.bayes.NaiveLearner, name='small', m=5): self.