Research on the Application of Decision Tree Algorithm in Agricultural Economic Development

As technology continues to advance, data analytics and machine learning have become key drivers of innovation across industries. In the field of agriculture, decision tree algorithms, as an efficient and easy-to-interpret machine learning technology, are gradually changing the face of the traditional agricultural economy and bringing far-reaching impacts to agricultural production.A decision tree is a tree-like structure model that mimics the human decision-making process, and it can predict future outcomes by learning from historical data. The algorithm selects the best attributes for splitting to construct a tree-like structure, and then classifies or regresses the new data. In the agricultural economy, decision tree algorithms can effectively help farmers and enterprises make more informed decisions, improve production efficiency, and optimize resource allocation.