WaveML / H2O-3 / Algo
Configure a specific algo for Wave Models built using H2O-3 AutoML.
from h2o_wave import main, app, Q, ui, copy_expandofrom h2o_wave_ml import build_model, ModelType
from sklearn.datasets import load_winefrom sklearn.model_selection import train_test_split
@app('/demo')async def serve(q: Q): if q.args.train: # train WaveML Model using H2O-3 AutoML copy_expando(q.args, q.client) q.client.wave_model = build_model( train_df=q.client.train_df, target_column='target', model_type=ModelType.H2O3, _h2o3_max_runtime_secs=30, _h2o3_nfolds=2, _h2o3_include_algos=[q.client.algo] ) model_id = q.client.wave_model.model.model_id accuracy = round(100 - q.client.wave_model.model.mean_per_class_error() * 100, 2)
# show training details and prediction option q.page['example'].items[1].choice_group.value = q.client.algo q.page['example'].items[2].buttons.items[1].button.disabled = False q.page['example'].items[3].message_bar.type = 'success' q.page['example'].items[3].message_bar.text = 'Training successfully completed!' q.page['example'].items[4].text.content = f'''**H2O AutoML model id:** {model_id} <br /> **Accuracy:** {accuracy}%''' q.page['example'].items[5].text.content = '' elif q.args.predict: # predict on test data preds = q.client.wave_model.predict(test_df=q.client.test_df)
# show predictions q.page['example'].items[3].message_bar.text = 'Prediction successfully completed!' q.page['example'].items[5].text.content = f'''**Example predictions:** <br /> {preds[0]} <br /> {preds[1]} <br /> {preds[2]}''' else: # prepare sample train and test dataframes data = load_wine(as_frame=True)['frame'] q.client.train_df, q.client.test_df = train_test_split(data, train_size=0.8)
# algos algo_choices = [ui.choice(x, x) for x in ['DRF', 'GLM', 'XGBoost', 'GBM', 'DeepLearning']]
# display ui q.page['example'] = ui.form_card( box='1 1 -1 -1', items=[ ui.text(content='''The sample dataset used is the <a href="https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_wine.html" target="_blank">wine dataset</a>.'''), ui.choice_group(name='algo', label='Select Algo', choices=algo_choices, value='DRF'), ui.buttons(items=[ ui.button(name='train', label='Train', primary=True), ui.button(name='predict', label='Predict', primary=True, disabled=True), ]), ui.message_bar(type='warning', text='Training will take a few seconds'), ui.text(content=''), ui.text(content='') ] )
await q.page.save()