Orange Blog

By: AJDA, Mar 23, 2016

All I See is Silhouette

Silhouette plot is such a nice method for visually assessing cluster quality and the degree of cluster membership that we simply couldn’t wait to get it into Orange3. And now we did. What this visualization displays is the average distance between instances within the cluster and instances in the nearest cluster. For a given data instance, the silhouette close to 1 indicates that the data instance is close to the center of the cluster.

By: BIOLAB, Dec 8, 2011

Random forest switches to Simple tree learner by default

Random forest classifiers now use Orange.classification.tree.SimpleTreeLearnerby default, which considerably shortens their construction times. Using a random forest classifier is easy. import Orange iris ='iris') forest = Orange.ensemble.forest.RandomForestLearner(iris, trees=200) for instance in iris: print forest(instance), instance.get_class() The example above loads the iris dataset and trains a random forest classifier with 200 trees. The classifier is then used to label all training examples, printing its prediction alongside the actual class value.