Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A two-layer neural network is developed in which the neu- ron model computes a user-defined similarity function beten inputs and ights. The neuron model is formed by the composition of an adapted lo- gistic function with the mean of the partial input-ight similarities. The model is capable of dealing directly with variables of potentially different nature (continuous, ordinal, categorical); there is also provision for missing values. The network is trained using a fast two-stage procedure and in- volves the setting of only one parameter. In our experiments, the network achieves slightly superior performance on a set of challenging problems with respect to both RBF nets and RBF-kernel SVMs.
['Lluís Belanche', 'Jerónimo Hernández']
I am writing a research paper on a idea Similarity networks for heterogeneous data
[{"from": "human", "value": "I am writing a research paper on a idea Similarity networks for heterogeneous data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A two-layer neural network is developed in which the neu- ron model computes a user-defined similarity function beten inputs and ights. The neuron model is formed by the composition of an adapted lo- gistic function with the mean of the partial input-ight similarities. The model is capable of dealing directly with variables of potentially different nature (continuous, ordinal, categorical); there is also provision for missing values. The network is trained using a fast two-stage procedure and in- volves the setting of only one parameter. In our experiments, the network achieves slightly superior performance on a set of challenging problems with respect to both RBF nets and RBF-kernel SVMs."}]