Application of E2M Decision Trees to Rubber Quality Prediction

Concerning the selection methods, as mentioned in section I, our aim is not to find the optimal subset of individual classifiers among a large ensemble of trees, but rather to

On DRD, retrieval precision based on all attributes is significantly higher than retrieval precision based on numerical attributes alone, at the 90% confidence level (but not on

Genetic transformation and regeneration of rubber tree (Hevea brasiliensis Muell. Arg) transgenic plants with a constitutive version of an anti-oxidative stress superoxide dismutase

The behavior of different clones of rubber trees facing the Loranthaceae parasitism has been studied in the large industrial plantation of Mitzic and in three neighboring

The first one is the classical decision tree learning algorithm for which the gain function is now based on possibilistic cumulative entropy.. In the next subsection we show that

A large number of extensions of the decision tree algorithm have been proposed for overfitting avoidance, handling missing attributes, handling numerical attributes, etc..

semanti deision tree editor, whih provides a ollaborative tool to sim-.. plify

To a person relatively unfamiliar with the field it provides a neat, curt insight into the historicaI aspects, different methods of training both on-the-job and