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08 Decision Tree Model

08 Decision Tree Model
Exercise: Decision Tree Model1.1) Partition the data into a training set (70%) and a test set (30%). Apply stratified sampling on the Gender column.1.2) Build a decision tree model to predict the gender category in the Gender column. Apply the model to the test set.1.3) Evaluate the model's performance with the Scorer (JavaScript) node. WA_American_Time_Use_Survey.csv70/30 splitstratified by TravelEvaluate modelPredict TravelNode 46CSV Reader Decision TreePredictor Partitioning Scorer (JavaScript) DecisionTree Learner Row Filter Exercise: Decision Tree Model1.1) Partition the data into a training set (70%) and a test set (30%). Apply stratified sampling on the Gender column.1.2) Build a decision tree model to predict the gender category in the Gender column. Apply the model to the test set.1.3) Evaluate the model's performance with the Scorer (JavaScript) node. WA_American_Time_Use_Survey.csv70/30 splitstratified by TravelEvaluate modelPredict TravelNode 46CSV Reader Decision TreePredictor Partitioning Scorer (JavaScript) DecisionTree Learner Row Filter

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Created by: Maarit Laukkanen
Created at: 2020-10-23
On NodePit since: 2022-02-05
Last update: 2024-05-01
Created with KNIME version: v4.5.1
Tags: classificationdecision treescorer

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