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The main advantage of the Verde API is that it handles the calculating of the sensitivity (feature) matrix and all the busy work of dealing with coordinates. Under the hood, it's all just linear models and the actual computations are passed along to scikit-learn. It would be to have a tutorial to show how to generate the feature matrix for a spline (Spline.jacobian) and then call scikit-learn directly on that in case people want to experiment with different fitting algorithms.
The text was updated successfully, but these errors were encountered:
The main advantage of the Verde API is that it handles the calculating of the sensitivity (feature) matrix and all the busy work of dealing with coordinates. Under the hood, it's all just linear models and the actual computations are passed along to scikit-learn. It would be to have a tutorial to show how to generate the feature matrix for a spline (
Spline.jacobian
) and then call scikit-learn directly on that in case people want to experiment with different fitting algorithms.The text was updated successfully, but these errors were encountered: