Soft decision trees
Year: 2012
Type: conference-paper
Abstract: We discuss a novel decision tree architecture with soft decisions at the internal nodes where we choose both children with probabilities given by a sigmoid gating function. Our algorithm is incremental where new nodes are added when needed and parameters are learned using gradient-descent. We visualize the soft tree fit on a toy data set and then compare it with the canonical, hard decision tree over ten regression and classification data sets. Our proposed model has significantly higher accuracy using fewer nodes.
Authors: İrsoy, Ozan, Yıldız, Olcay Taner, Alpaydın, Ahmet İbrahim Ethem
Institutions: Boğaziçi University, Işık University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2184406811