Support for decision trees
We’re happy to announce that PRSD Studio supports execution of decision trees trained in PRTools. Decision tree is a classifier trained feature-per-feature splitting the feature space into rectangular subspaces. The two key advantages of decision trees are interpretation capability (why was the decision made?) and speed. It is the speed of execution that makes decision tree classifier particularly interesting for industrial practitioners!
libPRSD Executing Support Vector classifiers trained in LIBSVM
LIBSVM is a powerful C library implementing Support Vector training and execution with interfaces to numerous scripting environment including Matlab. We’ve posted a Knowledge Base article showing how to bring a classifier, trained in LIBSVM, to the PRSD Studio and through it to custom applications. Executing SVC in libPRSD also brings significant speedup!
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