Decision Tree to Ruleset

Converts (a single) decision tree model to PMML RuleSet model and also to a table containing the rules in a textual form. The resulting rules are independent of each other, the order of rules is not specified, can be changed. Missing value strategies are ignored, it will always evaluate to missing value.

Options

Split rules to condition and outcome columns: When checked, two columns will be created for the rules, Condition and Outcome, otherwise the rules will reside in a single column, Rule.
Add confidence and weight columns: From PMML the confidence and weight attributes are extracted to columns. (It will create columns with missing values.)
Add Record count and Number of correct statistics columns: In PMML, the recordCount and the nbCorrect attributes provide statistics about the input (training/test/validation) data, with this option, this information can be extracted to the columns: Record count and Number of correct
Use additional parentheses to document precedence rules: If checked the output will contain additional parenthesis around rule parts to clearly document precedence. For instance, NOT is a stronger operator than AND than OR - using parenthesis improves readability. Checking this option does not change any of the rule logic.
Provide score distibution record count in PMML: PMML will store the information obtained from the rules on record counts of score distribution (how many times were the different values were present in the training data, not necessarily integer)
Provide score distibution record count in table with column name prefix: Information about the record count of score distribution is saved to the table with the specified prefix.
Provide score distibution probability in PMML: PMML will store the information obtained from the rules on probabilities of score distribution (in the training data what was the probability of certain values for that decision tree leaf)
Provide score distibution probability in table with column name prefix: Information about the probabilities of score distribution is saved to the table with the specified prefix

Input Ports

: A PMML Decision Tree model.

Output Ports

: The decision tree model represented as PMML RuleSets (with firstHit rule selection method).
: The table contains the rules' text (in single (Rule) or two columns (Condition, Outcome), the rule Confidence and Weight information and optionally the Record count (for how many rows did the ruleset matched when created) and Number of correct values where the outcome of the rule matched the expected label when the model was created.

Popular Predecessors

Popular Successors

Views

This node has no views

Workflows

Developers

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.

Installation

To use this node in KNIME, install the extension KNIME Javasnippet from the below update site following our NodePit Product and Node Installation Guide:

v5.4

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.4.0.v202407291249

On NodePit since: 2024-12-06

Last update: 2024-12-17

KNIME versions: Since v3.6

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!