1.

How are the time series problems different from other regression problems?

Answer»
  • Time series data can be thought of as an extension to linear regression which uses terms LIKE autocorrelation, movement of averages for summarizing historical data of y-axis variables for predicting a better future.
  • Forecasting and prediction is the MAIN goal of time series problems where accurate predictions can be MADE but sometimes the UNDERLYING reasons might not be known.
  • Having Time in the problem does not necessarily mean it becomes a time series problem. There should be a relationship between target and time for a problem to become a time series problem.
  • The observations close to one another in time are EXPECTED to be similar to the ones far away which provide accountability for seasonality. For instance, today’s weather would be similar to tomorrow’s weather but not similar to weather from 4 months from today. Hence, weather prediction based on past data becomes a time series problem.


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