From the course: Data Science Foundations: Data Assessment for Predictive Modeling

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Is the missing data worth saving?

Is the missing data worth saving?

From the course: Data Science Foundations: Data Assessment for Predictive Modeling

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Is the missing data worth saving?

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- [Instructor] Okay, we're back in KNIME with the same data set and the same workflow, but I've added several nodes because what we're about to do is a bit elaborate. It'll be easier to walk you through it, with the work done in advance. So our mission at the moment is to deal with the fact that we have several sections within our data set. And when one variable is missing, it usually means a dozen variables are missing. So let's take a closer look. I've added a row filter, and I've chosen one variable out of this section about magazines and so on, MBCRAFT, and I've checked to see if that's missing. And I'm going to exclude those rows that are missing. So if our understanding of the data is correct, I'm not just excluding MBCRAFT missing cases. Those cases will be missing on that whole section of variables. So in the column filter, so that I can focus on what I'm doing, I've got that whole section and our target…

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