Sample weights

import numpy as np
from mlforecast.utils import generate_daily_series

series = generate_daily_series(2)
series['weight'] = np.random.default_rng(seed=0).random(series.shape[0])
series.head(2)

import lightgbm as lgb
from sklearn.linear_model import LinearRegression

from mlforecast import MLForecast

fcst = MLForecast(
    models={
        'lr': LinearRegression(),
        'lgbm': lgb.LGBMRegressor(verbosity=-1),
    },
    freq='D',
    lags=[1],
    date_features=['dayofweek'],
)

fcst.fit(series, weight_col='weight').predict(1)

fcst.cross_validation(series, n_windows=2, h=1, weight_col='weight')