Communication Efficient Construction of Decision Trees Over Heterogeneously Distributed Data
Chris R. Giannella, Kun Liu, TO Olsen, H. Kargupta · 2005
We present an algorithm designed to efficiently construct a decision tree over heterogeneously distributed data without centralizing. We compare our algorithm against a standard centralized decision tree implementation in terms of accuracy as well as the communication complexity. Our experimental results show that by using only 20% of the communication cost necessary to centralize the data we can achieve trees with accuracy at least 80% of the trees produced by the centralized version.