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01_​DecisionTree

Decision Tree

Using the adult dataset, this workflow performs binary classification (income > or < 50K) using a Decision Tree. The target is the income column, either <=50K or <50K, predicted using the other demographic attributes. After partitioning the original dataset into training set and test, the decision tree is builkt on the training set and the final performance is evaluated on the test set using the Scorer node.

Binary classification problem (income >50K or <50K), solved using a decision tree 80% training20% teststratified samplingTrain DecisionTreePerformclassificationClassificationperformancecolor by sexRead theadult dataset Partitioning DecisionTree Learner Decision TreePredictor Scorer (JavaScript) Decision Treeto Ruleset Decision TreeView (JavaScript) Color Manager CSV Reader Binary classification problem (income >50K or <50K), solved using a decision tree 80% training20% teststratified samplingTrain DecisionTreePerformclassificationClassificationperformancecolor by sexRead theadult datasetPartitioning DecisionTree Learner Decision TreePredictor Scorer (JavaScript) Decision Treeto Ruleset Decision TreeView (JavaScript) Color Manager CSV Reader

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

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Created by: Emilio Silvestri
Created at: 2020-02-06
On NodePit since: 2024-04-10
Last update: 2024-05-01
Created with KNIME version: v5.2.3
Tags: TheGuideBookDecision TreeClassificationGIDS

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