sktime_naive_forecaster_train_test_split_mape_evaluation.py

1from sktime.datasets import load_airline
2from sktime.forecasting.base import ForecastingHorizon
3from sktime.forecasting.model_selection import temporal_train_test_split
4from sktime.forecasting.naive import NaiveForecaster
5from sktime.performance_metrics.forecasting import mean_absolute_percentage_error
6
7# Step 1: Load data
8y = load_airline()
9
10# Step 2: Split data into training and test sets
11y_train, y_test = temporal_train_test_split(y, test_size=36)
12
13# Step 3: Specify the forecasting horizon
14fh = ForecastingHorizon(y_test.index, is_relative=False)
15
16# Step 4: Fit a forecaster and make predictions
17forecaster = NaiveForecaster(strategy="last", sp=12)
18forecaster.fit(y_train)
19y_pred = forecaster.predict(fh)
20
21# Step 5: Calculate performance metrics
22mape = mean_absolute_percentage_error(y_test, y_pred)
23print(f"MAPE: {mape}")