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◈ EN | JP ◆

Lesson 12    ❮    Lesson List    ❮    Top Page


◆  Intro to Time Series


◆  Time Series Decomposition


◈  Smoothing-based Methods


◆  Regression-based Methods


◆  Machine Learning Methods


⟐  Implementation

See also the following links:

▎ENGLISH

Moving Average Smoothing for Data Preparation and Time Series Forecasting in Python
▸ https://machinelearningmastery.com/moving-average-smoothing-for-time-series-forecasting-python

Smoothing Techniques for time series data
▸ https://medium.com/@srv96/smoothing-techniques-for-time-series-data-91cccfd008a2

Holt-Winters Forecasting and Exponential Smoothing Simplified
▸ https://orangematter.solarwinds.com/2019/12/15/holt-winters-forecasting-simplified/

▎日 本 語

移動平均の計算方法
▸ https://bellcurve.jp/statistics/blog/15528.html

時系列及び波形データの平滑化3手法(smoothing)
▸ https://qiita.com/shota-imazeki/items/9428d29c41f63b906714

指数平滑化法
▸ https://hazm.at/mox/math/analysis/exponential-smoothing.html

©2023. All rights reserved.  Samy Baladram,
Graduate Program in Data Science - GSIS - Tohoku University
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