INSHAPE discovers instance-specific non-overlapping shapelets, models their temporal dependencies, and aggregates them bottom-up into population-level prototypes for improved accuracy and interpretability in time-series classification.
Interpretable heartbeat classification using local model-agnostic explanations on ecgs.Computers in biology and medicine, 133:104393,
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
-
INSHAPE: Instance-Level Shapelets for Interpretable Time-Series Classification
INSHAPE discovers instance-specific non-overlapping shapelets, models their temporal dependencies, and aggregates them bottom-up into population-level prototypes for improved accuracy and interpretability in time-series classification.