Abstract: Random Forest is a well-known type of ensemble learning, which combines a number of decision trees to improve the prediction ability and reduce the risk of overfitting. This paper aims at ...
Abstract: This study proposes a general multi-class hierarchical random network with an arbitrary number of agents and an arbitrary connecting success probability to analyze the minimum communication ...
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