MFLES 0.1.9

Gradient boosted time series forecasting.

MFLES

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:

Quick Start:

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()