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I am trying to perform topic modelling , it would be great to have a native LDA (latent dirichlet allocation) operator and also a Gradient Boost Operator.
rapidminer 7.2 added Gradient Boosted Trees as a new learner
Quoted from the operator help
A gradient boosted model is an ensemble of either regression or classification tree models. Both are forward-learning ensemble methods that obtain predictive results through gradually improved estimations. Boosting is a flexible nonlinear regression procedure that helps improving the accuracy of trees. By sequentially applying weak classification algorithms to the incrementally changed data, a series of decision trees are created that produce an ensemble of weak prediction models. While boosting trees increases their accuracy, it also decreases speed and human interpretability. The gradient boosting method generalizes tree boosting to minimize these issues
There is an LDA operator in the KobRA-Projekt extension at http://kobra.tu-dortmund.de/mediawiki/index.php?title=Software. The documentation is in German.
There's a corpus linguistics plugin 1.1.1 in Marketplace that should offer LDA functionality.
LDA is an extension but not updated (see here); Gradient Boosted Trees released in RM 7.2.
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