Imran Ali Syed's Workflows

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Type: Rapid Miner

Workflow Random Forest based Feature Weightage (1)

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Features can be assigned weightage through the random forest model. In this regard, RapidMiner's Auto Model comes quite handy. Divide the original data into training and testing datasets before applying the workflow to it.  

Created: 2020-06-30 | Last updated: 2020-06-30

Credits: User Imran Ali Syed

Workflow Gradient Boosting Trees based Feature Weig... (1)

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Features can be assigned weightage through the gradient boosting trees model. In this regard, RapidMiner's Auto Model comes quite handy. Divide the original data into training and testing datasets before applying the workflow to it. 

Created: 2020-06-30 | Last updated: 2020-06-30

Credits: User Imran Ali Syed

Workflow CHART based Feature Weightage (1)

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Features can be assigned weightage through the decision tree model. In this regard, RapidMiner's Auto Model comes quite handy. Divide the original data into training and testing datasets before applying the workflow to it. 

Created: 2020-06-30 | Last updated: 2020-06-30

Credits: User Imran Ali Syed

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