Is time series supervised or unsupervised?

A time series is an observation from the sequence of discrete-time of successive intervals . A time series is a running chart. The time variable/feature is the independent variable and supports the target variable to predict the results.

Time series forecasting can be framed as a supervised learning problem. This re-framing of your time series data allows you access to the suite of standard linear and nonlinear machine learning algorithms on your problem.

The Time Series mining function provides the following algorithms to predict future trends: Autoregressive Integrated Moving Average (ARIMA) Exponential Smoothing . Seasonal Trend Decomposition .

Autoregressive Integrated Moving Average (ARIMA ): Auto Regressive Integrated Moving Average, ARIMA, models are among the most widely used approaches for time series forecasting.22 Haz 2021