Which algorithm would be most appropriate for forecasting future sales based on historical data?
- Decision Trees
- K-Means Clustering
- Linear Regression
- Naive Bayes
Linear Regression is a suitable algorithm for forecasting future sales based on historical data. It models the relationship between the dependent variable (sales) and one or more independent variables (time, marketing spend, etc.), making predictions based on historical patterns.
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