Decision stream graph

Fig. 1. Decision stream: statistic-based merge of nodes from the same/different levels of predictive model.

File:Decision Stream vs. Binary Tree (32 nodes).pdfDecision stream is a directed acyclic graph of decision rules for classification and regression tasks (Fig. 1). This decision tree based method ^[1] avoids the problem of data exhaustion in terminal nodes by merging of leaves from the same/different levels of predictive model.

Decision stream provides:

– High accuracy due to the precise splitting of data with unpaired two-sample test statistics.

– Decrease of overfitting due to partition of data only into statistically representative groups.

– Reduction of complexity on every level of predictive model.

– Self-regulated depth of predictive model.

References

↑ Ignatov, D.Yu.. 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE Ictai (2017). p. 905–912. ISBN 978-1-5386-3876-7. doi:10.1109/ICTAI.2017.00140.