Predicting agricultural yields based on weather conditions and soil quality measurements is an example of a:
B. regression
Regression models are used for predicting continuous outcomes, such as yields, which can vary across a wide range of possible values based on the input variables like weather conditions and soil quality.
Incorrect Options:
A. Classification: This type of model would be used if you were categorizing data into discrete classes, like determining if a day is suitable for planting or not.
C. Clustering: This is used for grouping similar data points together without prior knowledge of the groups, and it's not typically used for prediction based on input variables.
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