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One of the advantage of the decision trees is that it ignore outliers. But how outliers come in the sense in case of decision trees. Because decision trees use a set of data like humidity, month, etc. It not uses the data like temperature, population, distance, etc. In this example how outliers can happen ?
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@Sanniddha Chakrabarti Thanks, Can you please share the input data and link to the code that you are trying.
No, I am not currently doing any ML code. I have learn about ML from Microsoft AI Classroom. But I have some doubt in the theory. My doubt is that in decision tress we use discrete values not continuous values. Then how outliers can happen in decision tress ? Can you give any example ?
@Sanniddha Chakrabarti Thanks, there are plenty of good resources online, presented as some guidelines like this one: https://towardsdatascience.com/how-to-tune-a-decision-tree-f03721801680
I have some doubt in the theory. My doubt is that in decision tress we use discrete values not continuous values. Then how outliers can happen in decision tress ? Can you give any example ?