Hello I am starting with Knime and I have created a workflow to evaluate different calcification algorithms. For my data, the best is Tree because a I have a good accuracy. My question is related about how can I understand the algorithm, and what are the fields of my data that have more influence in the prediction. I am trying to determine if a customer is going to leave the company and I have 50 fields in my database, but I don´t know what are more important fields to decide that a customers is going to leave. Is there any way to decide this? Ana

Understand Tree Decision

mlauber71 October 29, 2020, 8:06am 2

I recently wrote this entry. Maybe the links there might help you explore more about machine learning

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