Univariate time series: Only one variable is varying over time . For example, data collected from a sensor measuring the temperature of a room every second. Therefore, each second, you will only have a one-dimensional value, which is the temperature. Multivariate time series: Multiple variables are varying over time.
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What is Multivariate Forecasting ? If the model predicts dependent variable (y) based on one independent variable (x), it is called univariate forecasting. For Multivariate forecasting, it simply means predicting dependent variable (y) based on more than one independent variable (x) .
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