From the course: LinkedIn AI Academy AI-100: 1 Demystifying AI
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Multiple linear regression
From the course: LinkedIn AI Academy AI-100: 1 Demystifying AI
Multiple linear regression
- [Speaker] In the last video, we saw how linear regression is used to understand the relationship between the unknown variable and one observable variable. But often there are situations where we have multiple observable variables and a single unknown variable. To do this, we'll use a technique called Multiple Linear Regression. Continuing with our example of predicting conversations on an article, The observable variable that we have used in our previous section is a length of the article and we used the equation, y is equal beta not plus beta one X, but there are other variables that we could consider as well. For example, the average length of sentences in the article, a potential measure of readability which might also affect conversations. Let's name this variable, average sentence length, Z and then we can build a linear relationship between y, the conversations and x, the length of article and Z, the average…
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