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Time Series Forecasting

Time series forecasting is a method for predicting incidents over a long period of time. The strategies forecast potential events by observing historical patterns and assuming that future phenomena will follow in the footsteps of historical trends.

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Time Series Forecasting

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  1. TSF(Time Series Forecasting) - By learnbaydatascience institute

  2. Time Series Forecasting • Time series is a set of variables that ordered through time. • Making predictions about the future is called extrapolation in the classical statistical handling of time seriesdata. • Forecasting involves taking models fit on historical data and using them to predict future observations.

  3. Major 4 types of TSF(Time Series Forecasting) • Straight line: -Constant growth rate • Moving average: -repeated forecasts also known as seasonal forecasting • Simple linear regression: • -Compare one independent with one dependent variable. • Multiple linear regression: • -Compare more than one independent variable with one dependent variable.

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