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02_​Example_​for_​Predicting_​Time_​Series_​SF_​edit

Simple auto-regressive model to predict a time series

- Simple means just raw data: no seasonality correction, stationarity assumption
- Auto means usage of past of the same time series for prediction. No other exogenous time series/data used.
- Regressive refers to the model: either a linear or a polynomial regression

Simple auto-regressive model to predict a time series linear AR(lag)Here is where the time series gets selected andrenamed to "cluster"from x(t) to: x(t), x(t-1), x(t-2), ..., x(t-lag)read clusteredtime seriesreal vs. predictedfrom x(t) to: x(t), x(t-1), x(t-2), ..., x(t-lag) Partitioning Linear Regression Prepare Data Lag Column File Reader Line Plot Lag Column Simple auto-regressive model to predict a time series linear AR(lag)Here is where the time series gets selected andrenamed to "cluster"from x(t) to: x(t), x(t-1), x(t-2), ..., x(t-lag)read clusteredtime seriesreal vs. predictedfrom x(t) to: x(t), x(t-1), x(t-2), ..., x(t-lag) Partitioning Linear Regression Prepare Data Lag Column File Reader Line Plot Lag Column

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On NodePit since: 2022-02-06
Last update: 2024-11-21
Created with KNIME version: v4.1.2
Tags: time series

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