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What is Time Series Forecasting about?
Time series is a series of observations listed in the order of time. The data points in a time series are usually recorded at constant successive time intervals. Time series analysis is the process of extracting meaningful non-trivial information and patterns from time series. Time series forecasting is the process of predicting the future value of time series data based on past observations and other inputs. Time series forecasting is one of the oldest known predictive analytics techniques. It is widely used in every organizational setting and has deep statistical foundations. An example of a time series is shown in Fig. 12.1. It shows the time series value and period-monthly revenue of a product for a few years. Up to this point in this book, supervised model building has been about collecting data from several different attributes of a system and using these attributes to fit a function to predict a desired quantity or target variable. For example, if the system was a housing market, the attributes may have been the price of a house, location, square footage, number of rooms, number of floors, age of the house, and so on. A multiple linear regression model or a neural network mo
- Author
- Vijay Kotu; Bala Deshpande
- Published
- 2019
- Language
- EN
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