A Specific implementation from ThymeBoost written with the help of Numba.
Here is a quick Introduction:
https://github.com/tblume1992/MFLES/blob/main/examples/MFLES_Intro.ipynb
Here is a quick benchmark vs AutoETS from M4:
Install via pip
pip install MFLES
Import MFLES class
from MFLES.Forecaster import MFLES
Import data
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df = pd.read_csv(r'https://raw.githubusercontent.com/jbrownlee/Datasets/master/airline-passengers.csv')
Fit and predict!
mfles = MFLES()
fitted = mfles.fit(df['Passengers'].values, seasonal_period=12)
predicted = mfles.predict(12)
plt.plot(np.append(fitted, predicted))
plt.plot(df['Passengers'].values)
plt.show()