{"title":"Ruleset to Table","nodeType":"Manipulator","id":"*bDUBuscC47gFw7rG","factoryName":"org.knime.base.node.rules.engine.totable.RulesToTableNodeFactory","factoryId":"org.knime.base.node.rules.engine.totable.RulesToTableNodeFactory","path":["Manipulation","PMML"],"owner":"knime","ownerAccountId":"account:team:b5f0848f-496d-4e6a-b869-fa3532248db7","description":"<p>Converts PMML <a href=\"http://www.dmg.org/v4-2-1/RuleSet.html\" rel=\"ugc nofollow noopener noreferrer\">RuleSet</a> models (with <tt>firstHit</tt> rule selection method) to table containing the rules. This table is suitable for the Rule Engine (Dictionary) node as a rule input (even with PMML output generation). Use cases for this node: Convert the PMML model to ordinary table to</p><ul><li>concatenate different rule tables</li><li>(row) filter out certain outcomes</li><li>re-level/recode outcomes</li></ul>\n            \n        \n        ","shortDescription":"Converts PMML RuleSets (with firstHit) to table containing the rules.","keywords":[],"deprecated":false,"streamable":false,"tags":["Manipulation","PMML"],"icon":"data:image/png;base64,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","views":[],"inPorts":[{"objectClass":"org.knime.core.node.port.pmml.PMMLPortObject","color":"1469af","dataType":"PMML","optional":false,"name":"PMML ruleSet model","description":"The PMML RuleSet model."}],"outPorts":[{"objectClass":"org.knime.core.node.BufferedDataTable","color":"000000","dataType":"Table","optional":false,"name":"Rules table","description":"The table contains the rules&#39; text (in single ( <b>Rule</b> ) or two columns ( <b>Condition</b> , <b>Outcome</b> ), the rule <b>Confidence</b> and <b>Weight</b> information and optionally the <b>Record count</b> (for how many rows the ruleset matched when created) and <b>Number of correct</b> values"}],"dynInPorts":[],"dynOutPorts":[],"additionalSiteInformation":{"url":"https://update.knime.com/analytics-platform/5.12","trusted":true,"enabledByDefault":true,"name":"KNIME Analytics Platform 5.12 Update Site","version":"5.12.0"},"dialog":[{"sectionName":"Options","fields":[{"name":"Split rules to condition and outcome columns","description":"When checked, two columns will be created for the rules, &#34;Condition&#34; and &#34;Outcome&#34;, otherwise the rules will reside in a single column, &#34;Rule&#34;.","optional":false},{"name":"Add confidence and weight columns","description":"From PMML the confidence and weight attributes are extracted and added as separate columns to the output table.","optional":false},{"name":"Add record count and number of correct statistics columns","description":"In PMML, the &#34;recordCount&#34; and the &#34;nbCorrect&#34; attributes provide statistics about the input (training/test/validation) data. When checked, this information is extracted into &#34;Record count&#34; and &#34;Number of correct&#34; columns.","optional":false},{"name":"Use additional parentheses to document precedence rules","description":"If checked, the output will contain additional parentheses around rule parts to clearly document operator precedence. For instance, NOT is a stronger operator than AND which is stronger than OR — using parentheses improves readability. This option does not change any rule logic.","optional":false},{"name":"Provide score distribution record count","description":"When checked, information about the record count of score distribution is added to the output table. The column names are prefixed with the specified prefix.","optional":false},{"name":"Record count column name prefix","description":"Column name prefix used for the score distribution record count columns in the output table.","optional":false},{"name":"Provide score distribution probability","description":"When checked, information about the probabilities of score distribution is added to the output table. The column names are prefixed with the specified prefix.","optional":false},{"name":"Probability column name prefix","description":"Column name prefix used for the score distribution probability columns in the output table.","optional":false}]}],"links":[],"kudos":[],"kudosCount":0,"bundleInformation":{"bundleVersion":"5.12.0.v202606171353","bundleName":"KNIME Java Snippet Nodes","bundleSymbolicName":"org.knime.jsnippets","bundleVendor":"KNIME AG, Zurich, Switzerland","featureSymbolicName":"org.knime.features.javasnippet","featureName":"KNIME Javasnippet","featureVersion":"5.12.0.v202606171353","featureVendor":"KNIME AG, Zurich, Switzerland","extensionId":"*hXfYFyb7ZzM0xseG"},"frequentSuccessors":[{"id":"*0Y5y2-u7yUx5ohSu","factoryName":"org.knime.base.node.rules.engine.pmml.PMMLRuleEditorNodeFactory","probability":0.2727272727272727},{"id":"*OF3oP5KCNWP8Fkn2","factoryName":"org.knime.base.node.rules.engine.pmml.PMMLRuleSetPredictorNodeFactory","probability":0.13636363636363635},{"id":"*GpUdH91fJl4_KfiB","factoryName":"org.knime.base.node.rules.engine.twoports.RuleEngine2PortsNodeFactory","probability":0.09090909090909091},{"id":"*DrXVUHMX1uH3lVqD","factoryName":"org.knime.base.node.image.tablerowtoimage.TableRowToImageNodeFactory","probability":0.045454545454545456},{"id":"*jd2U-FYTI8jCbQls","factoryName":"org.knime.base.node.preproc.filter.row.RowFilterNodeFactory","probability":0.045454545454545456},{"id":"*JiJhJpgkWWuOfG2s","factoryName":"org.knime.ext.poi2.node.write2.XLSWriter2NodeFactory","probability":0.045454545454545456},{"id":"*j-Kmco8ue7gKNE7e","factoryName":"org.knime.ext.md.RuleViewerNodeFactory","probability":0.045454545454545456},{"id":"*pUuELUhDh08r8wjt","factoryName":"org.knime.base.node.preproc.rounddouble.RoundDoubleNodeFactory","probability":0.045454545454545456},{"id":"*s_n_DfFCBZqzUJsJ","factoryName":"org.knime.ext.birt.nodes.pdf.PdfReportNodeFactory","probability":0.045454545454545456},{"id":"*uLyMaZRk4kf96S85","factoryName":"org.knime.base.node.meta.looper.recursive.RecursiveLoopEndNodeFactory","probability":0.045454545454545456}]}