Hello,
From the documentation, I understand that I can get the predicted accuracy by looking at “scores_” in the fitted searchlight object. For example
pipeline = make_pipeline(StandardScaler(), SVR(kernel = 'linear'))
searchlight_state = nilearn.decoding.SearchLight(mask, process_mask_img=mask, scoring = "explained_variance", estimator = pipeline, radius=4, n_jobs=24, verbose=0, cv=LeaveOneOut())
searchlight_state.fit(fmri_img, sE, runs)
mean_fmri = nilearn.image.mean_img(fmri_img)
score_img = new_img_like(mean_fmri, searchlight_state.scores_)
My question is, can I retrieve the predicted label, the predicted y value, or the probability for each label?
Thanks,
Kai