Title: Time Series Forecasting in Python
Have data from 2018-07 to 2020-10, now need to use the history to forecast the future period of data to have the lowest MAPE value. You can change the parameters: 'time series', 'changepoint_prior_scale', 'seasonality_mode', 'growth', 'model', and 'horizon'. How can I get a reasonable and lower MAPE value?
Below is the code:
```python
# Remove history
is_limitedHistory = timeSeries['ds'] >= '2020-01-01'
timeSeriesLimitedHistory = timeSeries[is_limitedHistory]
# Tune and calculate MAPE
model = Prophet(changepoint_prior_scale=0.077, seasonality_mode='multiplicative', growth='linear')
model.fit(timeSeriesLimitedHistory)
validationData = cross_validation(model, horizon='35 days', cutoffs=forecast_start)
errorMetrics = performance_metrics(validationData)
MAPE = errorMetrics['mape'].mean(axis=0)
MAPE
```