Minimising Decision Tree Size as Combinatorial Optimisation?

Reducing the Number of Binary Splits, in Decision Tree Induction, by means of an Hierarchical Classification. Israël-César Lerman, Joaquim

Experimental results on 13 benchmark datasets showed that the proposed approach allows constructing efficient DTs that o↵er very high accuracy and F-measure results while

Finally, we obtain two more CART-based models using the independent parameters, which are detected (recognized) as important parameters. Further highlighting the

salperwy/index.php?id=moa-extension.. • HTNB: Hoeffding Tree using a na¨ıve Bayes - This version is identical to the previous one but possesses a na¨ıve Bayes classifier in the

Development of an intelligent agent-based model of the epidemic process of syphilis, International Scientific and Technical Conference on Computer Sciences and

Our verification algorithm of ensembles of decision trees: (1) is domain agnostic, since it can be instantiated to any abstract domain which represents properties of real vectors,

Secondly, we suggest a quantum version of this algorithm, which uses quantum sub- routines like the amplitude amplification and the D¨ urr-Høyer minimum search algorithms that are

1) Decision Tree: A decision tree is a (graphical) method of supporting the decision-making process. It is used in decision theory and in machine learning. In the second application,