// //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Load the data and split it into separate pieces
data = pm.datasets.load_wineind()
train, test = data[:150], data[150:]
// Fit a simple auto_arima model
arima = pm.auto_arima(train, error_action="ignore", trace=True,
suppress_warnings=True, maxiter=10,
After Change
// //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// Load the data and split it into separate pieces
data = pm.datasets.load_wineind()
train, test = model_selection.train_test_split(data, train_size=150)
// Fit a simple auto_arima model
arima = pm.auto_arima(train, error_action="ignore", trace=True,
suppress_warnings=True, maxiter=10,
