This node computes the informational entropy of each term in each document. The nodes requires a bag of words table as input and appends an additional column to the output table, containing the entropy values. If a term occurs once in every document, its entropy for each document is 0. Any other combination of frequencies determines an entropy weight between 0 and 1. Please note, that the computational complexity of of the entropy calculation is greater than the number of terms times the number of documents. For big bag of words input tables the computation can be quite time consuming.
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.
A zipped version of the software site can be downloaded here.
Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.Try NodePit Runner!
Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to firstname.lastname@example.org, follow @NodePit on Twitter or botsin.space/@nodepit on Mastodon.
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.