Classification is a machine learning approach to automatically assign a category to data records, where the categories can be binary values, such as good/bad, or can consist of multiple values. The basis for training a classifier is a large enough that constitutes the ground-truth, i.e., information about how the data should be labeled. Data can be, for instance, documents, sensor measurements or customer records to determine, for instance, the presumed relevance of documents or customers with a high-probability of churn.
A dataset with label information.
Report on the accuracy and applicability of different classification techniques.
The costs amount to 5.000€+VAT. You can also take advantage of the Lab bonus, which covers 50% to 65% of the incurred costs.
Markus Zanker is an associate professor at the Faculty of Computer Science of the Free University of Bozen-Bolzano. Find out more about him checking out his website.
We have created a diagram that displays common keywords from articles written by Markus Zanker. This is often useful to see what the respective researcher is doing: click here.
Artificial intelligence, Machine learning