The simple exponential smoothing method for forecasting is different from the simple moving averages method for which of the following reasons?   Question 25 options:   It allows for forecasting with time series data demonstrating a linear trend   It provides forecasts that are weighted averages of all the previous actual values of the time series   It captures seasonality in time series data in a more accurate manner.   It requires more time periods to be considered for forecasting a current period

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Temporal difference learning

Temporal difference learning (TD learning) is a concept in machine learning that attributes to a class of model-free reinforcement learning methods. The technique predicts a reward or quantity depending on the future values of the value function.