Combining decision tree and Bayesian networks for improved predictive analytics
Abstract
This chapter explores the dynamic combination of decision trees and Bayesian networks (BNs) in predictive analytics. At the heart of the research problem is the need for precise and intelligible predictive models. To accomplish this, we combine the skills of decision trees in capturing complicated patterns with the strengths of BNs in modeling probabilistic dependencies. Our goals include demonstrating the motivation for this integration, emphasizing its usefulness in data-driven decision-making across multiple industries, and providing a clear summary of the functioning mechanism. The strategies mentioned include combining ...
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