Sunday, February 28, 2021
Home Tech & Gadget How to turn your dog’s nap time into a regularized linear model

How to turn your dog’s nap time into a regularized linear model

Looking at this nap time pattern, Beta 0 is the intercept, the value taken by the target when all features are zero.

The remaining betas are the unknown coefficients which, along with the interception, are the missing pieces of the model. You can observe the result of combining the different features, but you don’t know all the details about the impact of each feature on the target.

Once you determine the value of each coefficient, you know the direction, positive or negative, and the magnitude of the impact of each entity on the target.

With a linear model, you assume that all the features are independent of each other, for example, the fact that you received a delivery has no impact on the number of treats your dog receives per day.

Additionally, you think there is a linear relationship between functionality and target.

So on the days when you play with your dog more, he will be more tired and want to nap longer. Or, on days when there are no squirrels outside, your dog won’t need to nap as much because he hasn’t expended so much energy to stay alert and watch every move. squirrels.

How long will your dog take a nap tomorrow?

With the general idea of ​​the model in mind, you collected data for a few days. You now have real observations on the characteristics and target of your model.