Alois P. Heinz

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| We propose the lazy neural tree (LNT) as the appropriate architecture for the realization of smooth regression systems. The LNT is a hybrid of a decision tree and a neural network. From the neural network it inherits smoothness of the generated function , incremental adaptability, and conceptual simplicity. From the decision tree it inherits the topology(More)
Ntree is a C library of tools for the construction, training, and evaluation of Neural Trees. It contains an improved version of the CART algorithm for the construction of binary decision trees that incorporate splits with respect to fuzzy sets. These trees can be regarded as (or translated to) Neural Trees. For their training the Ntree library implements(More)
We propose Adaptive Fuzzy Neural Trees as an appropriate tool for intelligent data analysis, comprehension , and prediction. Instead of using a single technique Adaptive Fuzzy Neural Trees as a mixture of paradigms combine the main advantages of neural networks, decision trees, and fuzzy logic. Like neural networks they are able to model smooth functions(More)