Bayes Risk Consistency of Nonparametric Classification Rules for Spike Trains Data. (arXiv:2308.04796v1 [cs.IT])

Spike trains data find a growing list of applications in computational
neuroscience, imaging, streaming data and finance. Machine learning strategies
for spike trains are based on various neural network and probabilistic models.
The probabilistic approach is relying on parametric or nonparametric
specifications of the underlying spike generation model. In this paper we
consider the two-class statistical classification problem for a class of spike
train data characterized by nonparametrically specified intensity functions. We
derive the optimal Bayes rule and next form …

applications arxiv bayes classification computational computational neuroscience data finance imaging list machine machine learning network neural network neuroscience parametric risk rules strategies streaming streaming data trains