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Using parameters in regression models

Using parameters in regression models - Power BI Tutorial

From the course: Power BI: Integrating AI

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Using parameters in regression models

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- [Instructor] Once we calculate the regression results, we can analyze metrics like the coefficient of determination and the F statistic to determine if the regression model is a good fit. Parameters and power BI models let us ask what-if questions about our data. Within AI models, we can use them to explore the impact of changing a model threshold, to test a regression fit on a filtered dataset, or to input new data to see what its predicted outcome label will be. We can calculate the F statistic for a polynomial regression model by copying the standard error formula. We'll then create two new measures. And our select column statement will return the FStatistic. We can go to the polynomial regression table if we want to see what the names of the fields that we want to select are. Let's then copy our F statistic formula and use it to calculate R squared, where we're going to refer to the coefficient of determination column from our coefficients results. Let's then add both of these…

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