Evolving lifted data vectors under a chaotic dynamical system before softmax classification accelerates training and improves accuracy over standard and lifted-only baselines on perturbed orthogonal vectors.
Evaluating machine learning classification for financial trad- ing: An empirical approach.Expert Systems with Applications, 54:193– 207
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Enhancing classification accuracy through chaos
Evolving lifted data vectors under a chaotic dynamical system before softmax classification accelerates training and improves accuracy over standard and lifted-only baselines on perturbed orthogonal vectors.