KernelPCA also has a fit_inverse_transform parameter but the situation is a bit different because we need the training data, which is only available in fit. Here, the situation is different because we only need the unmixing matrix.

If we want to keep inverse_transform side-effect free, we can just recompute the mixing matrix every time.