This unit introduces the concept of additive decomposition, a method for breaking down time series data into its trend, seasonal, and residual components. Students will learn the techniques and applications of additive decomposition in the context of machine learning. Üben mit sofortiger Rückmeldung, kostenlos und ohne Anmeldung.

Weitere Themen

• Definition and Overview
• Types of Time Series Data
• Applications of Time Series Analysis
• Multiplicative Decomposition
• Stationarity and Differencing
• Naive Forecasting
• Moving Average Forecasting
• Exponential Smoothing Forecasting