This workflow is part of a number of other workflows that address a data mining scenario at the intersection of active learning, text mining, stream mining and service-oriented knowledge discovery architectures. In particular, this workflow trains two models. A Document Vector Model depending on the keywords extracted from the training set during the pre-processing step and a Random Forest model that makes the predictions of the document_class. The models created at this stage can be used later on in the active learning cycle (Re-label_Uncertain_Classes workflow).
EXAMPLES Server: 50_Applications/33_Emil_the_TeacherBot/01_Initial_Model_Training50_Applications/33_Emil_the_TeacherBot/01_Initial_Model_Training*
Download a zip-archive
* Find more about the Examples Server here.
The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher). In other cases, please use the link to a zip-archive or open the provided path manually