While doing machine learning projects we've heard that logistic regression works well with "Linear data" and decision tree works well with "non-linear data"
However concept of linear and non-linear data does not make sense. To me only linearly separable data and non-linearly separable data makes sense to me, it only makes sense to say logistic regression works well with "Linearly separable data" since it is a linear function. In mathematics linear functions are polynomials with degree one and all other functions that are not linear are considered non-linear function.
What exactly is linear data and non-linear data?