This category contains 16 nodes.
This class implements a single conjunctive rule learner that can predict for numeric and nominal class labels. A rule consists of antecedents "AND"ed […]
Class for building and using a simple decision table majority classifier. For more information see: Ron Kohavi: The Power of Decision Tables
Class for building and using a decision table/naive bayes hybrid classifier
FURIA: Fuzzy Unordered Rule Induction Algorithm Details please see: Jens Christian Huehn, Eyke Huellermeier (2009)
This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W
Implements the LAC (Lazy Associative Classifier) algorithm, which uses associative rules to execute classifications
Generates a decision list for regression problems using separate-and-conquer
Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules)
This class is an implementation of the Ordinal Learning Method (OLM). Further information regarding the algorithm and variants can be found in: Arie […]
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 chat on Gitter!
Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.