The Annotator

by Algolit

The annotator asks for the guidance of the visitor in annotating the archive of Mundaneum.

The annotation process is a crucial step in supervised machine learning where the algorithm is given examples of what it needs to learn. A spam filter in training will be fed examples of spam and real messages. These examples are entries, or rows from the dataset with a label depending the task at hand, spam/not-spam, human/machine etc. in this process humans label or classify entries from the dataset. Once enough samples of each label have been gathered in the dataset, the computer can start the learning process.

In this interface we ask you to help us classify the cleaned entries from the Mundaneum archive as human or machine, future or past to expand our training set and improve the quality of our model.

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Concept, code, interface: Gijs de Heij

Technique: Naive Bayes