#%%[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