def apply_model_to_data(model: Chain, data_path: str):
df, file_path = create_multi_clf_examples_from_excel(data_path,
return_df=True)
dataset_to_apply = InputData.from_csv(file_path, target_column=None)
evo_predicted = model.predict(dataset_to_apply)
df['forecast'] = probs_to_labels(evo_predicted.predict)
return df
def test_chain_with_datamodel_fit_correct(data_setup):
data = data_setup
train_data, test_data = train_test_data_setup(data)
chain = Chain()
node_data = PrimaryNode('logit')
node_first = PrimaryNode('bernb')
node_second = SecondaryNode('rf')
node_second.nodes_from = [node_first, node_data]
chain.add_node(node_data)
chain.add_node(node_first)
chain.add_node(node_second)
chain.fit(train_data)
results = np.asarray(probs_to_labels(chain.predict(test_data).predict))
assert results.shape == test_data.target.shape