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titanic-rf1

Training a Random Forest

Training a decision tree and training a random forest of decision trees.

500 dec treesmin node size = 2Read the datasetNode 25Node 26Node 27Node 28Node 29Node 31Node 32Random ForestLearner Random ForestPredictor Scorer (JavaScript) File Reader Tree EnsembleModel Extract Table to PMMLEnsemble Tree EnsembleStatistics Extract TableDimension Number ToString (PMML) CSV Reader(deprecated) Partitioning JPMML Classifier CSV Writer(deprecated) Column Filter 500 dec treesmin node size = 2Read the datasetNode 25Node 26Node 27Node 28Node 29Node 31Node 32Random ForestLearner Random ForestPredictor Scorer (JavaScript) File Reader Tree EnsembleModel Extract Table to PMMLEnsemble Tree EnsembleStatistics Extract TableDimension Number ToString (PMML) CSV Reader(deprecated) Partitioning JPMML Classifier CSV Writer(deprecated) Column Filter

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Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: kathrinmelcher
Created at: 2017-09-14
On NodePit since: 2020-12-07
Last update: 2024-04-25
Created with KNIME version: v4.3.0
Tags: classificationmachine learningpredictionanalyticsKNIMEdecision treedata scienceC4.5CARTrandom forestbaggingensemble models

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