Biased Hypothesis Formation From Projection Pursuit. (arXiv:2201.00889v1 [cs.LG])

The effect of bias on hypothesis formation is characterized for an automated
data-driven projection pursuit neural network to extract and select features
for binary classification of data streams. This intelligent exploratory process
partitions a complete vector state space into disjoint subspaces to create
working hypotheses quantified by similarities and differences observed between
two groups of labeled data streams. Data streams are typically time sequenced,
and may exhibit complex spatio-temporal patterns. For example, given atomic
trajectories from molecular dynamics simulation, the …

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