text: Title: What does it mean? [ValueError: Cannot build a single input for prediction with the provided model]
  Body: I have this single component data set. This returns the following error.
  
  > ValueError: Cannot build a single input for prediction with the provided model, `series` and `*_covariates` at series index: 0. The minimum prediction input time index requirements were not met. Please check the time index of `series` and `*_covariates`.
  
  Here is the code snippet. The df has 14 days of data. I am interested if there is any anomaly in the last 1 day. Time interval of the data is 5 mins. **What am I missing?**
  
  ```python
  df = pd.DataFrame(rsp_data['USER_BUSY_STATS'], columns=['value', 'timestamp'])
  
  
  last_288th_row = df['timestamp'].iloc[-288]
  
  
  first_row = df['timestamp'].iloc[0]
  
  
  last_row = df['timestamp'].iloc[-1]
  
  
  
  series = TimeSeries.from_dataframe(df, time_col='timestamp', value_cols='value')
  
  plt.plot(df['timestamp'], df['value'], label='value')
  
  from darts.ad.anomaly_model.forecasting_am import ForecastingAnomalyModel
  
  anomaly_model = ForecastingAnomalyModel(
      model=LinearRegressionModel(lags=288),
      scorer=KMeansScorer(k=2, window=288),
  )
  
  train = series.slice(start_ts=first_row, end_ts=last_288th_row)
  test = series.slice(start_ts=last_288th_row, end_ts=last_row)
  
  anomaly_model.fit(
      series=train,
      forecast_horizon=288,
      allow_model_training=True)
  
  model_forecasting = anomaly_model.score(
      series=test,
      return_model_prediction=True,
      forecast_horizon=288
  )
  
  print(f"On testing set -> MAE: {mae(model_forecasting, test)}, RMSE: {rmse(model_forecasting, test)}")
  
  
  anomaly_model.show_anomalies(
      series=test,
      metric="AUC_ROC"
  )
  plt.show()
  ```
  
  
  