I was wondering if anyone could provide me some insight into the difference between fit and fit_transform for connectivity measure.
When trying to fit an SVM as in the example, the connectivity matricies must be produced at the time of running the SVM. If I run through all of my subjects files and store the connectivity matricies using fit_transform & python pickle, the results are drastically different to when I fit_transform the training set and fit the test set. https://nilearn.github.io/auto_examples/03_connectivity/plot_group_level_connectivity.html#sphx-glr-auto-examples-03-connectivity-plot-group-level-connectivity-py
Does anyone know of a way of storing these so that they do not need to be recalculated?