预测回调

import copy

import lightgbm as lgb
import numpy as np
from IPython.display import display

from mlforecast import MLForecast
from mlforecast.utils import generate_daily_series

series = generate_daily_series(1)

def inspect_input(new_x):
    """Displays the model inputs to inspect them"""
    display(new_x)
    return new_x

fcst = MLForecast(lgb.LGBMRegressor(verbosity=-1), freq='D', lags=[1, 2])
fcst.fit(series, static_features=['unique_id'])
preds = fcst.predict(2, before_predict_callback=inspect_input)
preds

from mlforecast.callbacks import SaveFeatures

fcst = MLForecast(lgb.LGBMRegressor(verbosity=-1), freq='D', lags=[1])
fcst.fit(series, static_features=['unique_id'])
save_features_cbk = SaveFeatures()
fcst.predict(2, before_predict_callback=save_features_cbk);

save_features_cbk.get_features()

def increase_predictions(predictions):
    """Increases all predictions by 10%"""
    return 1.1 * predictions

fcst = MLForecast(
    {'model': lgb.LGBMRegressor(verbosity=-1)},
    freq='D',
    date_features=['dayofweek'],
)
fcst.fit(series)
original_preds = fcst.predict(2)
scaled_preds = fcst.predict(2, after_predict_callback=increase_predictions)
np.testing.assert_array_less(
    original_preds['model'].values,
    scaled_preds['model'].values,
)