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RE: Webcast Into Data Science: Understanding Decision Trees Follow-up

Definitively it involves more than just decision trees. Take for example random forests. They divide they attributes randomly between multiple trees and then another algorithm figures out how to weigh each result to arrive at an overall decision. The nice thing about this is that you only need...


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RE: Webcast Into Data Science: Understanding Decision Trees Follow-up

When I said that decision trees were simple, I did not mean it is a simple form of ML. I meant that they are easily understood. They are also transparent in the sense that we can figure out how we got to a decision. When you ask about the situation where decision trees are not sufficient, you...


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RE: Webcast Into Data Science: Understanding Decision Trees Follow-up

Hello Jacques, Ensembles need not necessarily be all decision trees; could be a decision tree and different algorithm(s), right? Thank you! -- Rajagopal Krishnarjunan --


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RE: Webcast Into Data Science: Understanding Decision Trees Follow-up

Hi Jacques, In the webinar, you said I reckon that decision trees are a simple form of ML. What if decision trees are not sufficient, how should one proceed if that's the case? Thanks! -- Henri Ajenstat --


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Webcast Into Data Science: Understanding Decision Trees Follow-up

Thank you everyone for attending today's webcast! In this webcast we covered decision trees:<o:p></o:p> What are they?<o:p></o:p> What are they good for?<o:p></o:p> Decision trees limitations<o:p></o:p> Types of decision trees<o:p...