Abstract-We introduce a kernel for structured data, which is an extension of the Fisher Kernel used for sequences [11]. In our approach, we extract the Fisher score vectors from a Bayesian Network, specifically a Hidden Tree Markov Model [6], which can be constructed starting from the training data. Experiments on a QSPR (quantitative structure-property relationship) analysis, where instances are naturally represented as trees, allow a first test of the approach.

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