from MLP import get_single_mlp, compile_model, train_model, auto_fit, select_best_model # Datasource settings filename = "../data/Titanic_train.csv" target = 'Survived' ignore_fields = ['Name', 'Cabin', 'Ticket'] # Network settings use_all = False hidden_layers = [1, 2] units = [16, 32] optimizers = ['adam'] lrs = [0.01] ds = DataSource(filename) ds.data_load_split(target=[target], ignore=ignore_fields) ds.define_problem() ds.train_val_split(ratio=0.2, random_state=42) ds.data_preprocess(ds.X_train, ds.y_train, train_set=True) ds.data_preprocess(ds.X_val, ds.y_val, train_set=False) X_train, y_train = ds.trans_X_train, ds.trans_y_train X_val, y_val = ds.trans_X_val, ds.trans_y_val def train(hidden_layers, units, optimizers, lrs, use_all=False): # fit models start_time = time.time() models, param_info, val_losses = auto_fit(ds.problem, X_train,