#%%[markdown] # ### Jupyter notebook detection # # Check if running inside Jupyter notebook or not (will be used later for Keras progress bars) #%% in_ipynb = check_ipynb().is_inipynb() #%%[markdown] # ### Data # # Load the data #%% d = data() d.load_data(restrict_data=RESTRICT_DATA, restrict_sample_size=RESTRICT_SAMPLE_SIZE) #%%[markdown] # ### PSE helper functions #%% phf = pse_helper_functions() pse_pp = phf.pse_pp pse_a = phf.pse_a #%%[markdown] # ### Cross-validation # # Do the cross validation. This is a single cell to avoid # problems if exeution stops. The code is commented to
# ### Data # # Load the preprocessed data of the evaluation set #%%[markdown] # #### Load the data #%% hp = joblib.load(os.path.join(save_path, 'hp.joblib')) if len(hp) == 3: BATCH_SIZE, SEQUENCE_LENGTH, W2V_EMBEDDING_DIM = hp elif len(hp) == 4: _, BATCH_SIZE, SEQUENCE_LENGTH, W2V_EMBEDDING_DIM = hp d = data(subset='test') d.load_data(get_profiles=False) #%%[markdown] # #### Make the data lists #%% _, targets, seqs, active_meds, depas, _, _, _, _ = d.make_lists( get_valid=False) #%%[markdown] # ### Word2vec embeddings # # Load the previously fitted word2vec pipeline