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Combining Anatomical and Functional Networks for Neuropathology Identification: A Case Study on Autism Spectrum Disorder
Finally, we use these new markers to train a decision tree, an interpretable classification scheme, which results in a final diagnosis aid model.
A One-Class Classification Decision Tree Based on Kernel Density Estimation
Within a greedy and recursive approach, our proposal rests on kernel density estimation to split a data subset on the basis of one or several intervals of interest.
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