Decision stream graph

Decision 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.

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

Fig. 2. Binary decision stream and tree with the same quantity of nodes.

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.