Okay for all these regression model, we can actually evaluate are these our regression model using something like this. So, let's say for the model is species for simple linear regression we can only use all those are numeric variables. So, I will predict I say sepal length sepal length to set away and they tie a train segment holidays I can remove and I can look into the model for prediction I do not need to control a and then run so, I have bodies are model here. So, if I want to look into the accuracy of this model, I can do something that is summary model, then I have the R square and all the residue errors. So, now I bought a residue coefficients and I should add multiple r square here. So, what this means is that, if this value is a to us or nearer to one, then the model is is of higher or better accuracy.

So, for here this model is not that accurate. So, we can use our these r square to actually evaluate our regression model