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Ingest TS2Vec, and cap the probe as the authors do - #24

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Ingest TS2Vec, and cap the probe as the authors do#24
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61 of 66 datasets. EmoPain is the archive-wide input-validation failure. The other four, AustraliaRainfall_disc, Locust2022, Tiselac and USCActivity, timed out at exactly the 60 hour limit using about 3 GB, so time rather than memory.

The cause is a gap in this port. The authors' fit_svm subsamples to MAX_SAMPLES=10000 with stratification before the grid search and returns the estimator fitted on that subsample; fit_lr does the same at 100000. This wrapper reimplemented the probe and omitted the cap, so on the large collections it ran ten values of C over five folds of an RBF SVC on the whole training set, which is between quadratic and cubic in the number of cases. probability=True, needed for predict_proba, adds internal Platt folds on top.

Added probe_max_samples, defaulting to the authors' values, and probe_cases_ records what the probe was actually fitted on. The four timeouts are rerunnable, and the missing_results rows say so rather than recording them as a property of the method.

TS2Vec lands 20th of 26 on rank, mean accuracy 0.7212, which is above TimesURL, the fork of it already in the archive.

Summary

  • What does this PR change?

Checklist

  • I have updated documentation if needed.
  • I have added tests or validation steps if needed.
  • If this PR submits results, it follows results/schema.md.

61 of 66 datasets. EmoPain is the archive-wide input-validation failure. The
other four, AustraliaRainfall_disc, Locust2022, Tiselac and USCActivity, timed
out at exactly the 60 hour limit using about 3 GB, so time rather than memory.

The cause is a gap in this port. The authors' fit_svm subsamples to
MAX_SAMPLES=10000 with stratification before the grid search and returns the
estimator fitted on that subsample; fit_lr does the same at 100000. This
wrapper reimplemented the probe and omitted the cap, so on the large
collections it ran ten values of C over five folds of an RBF SVC on the whole
training set, which is between quadratic and cubic in the number of cases.
probability=True, needed for predict_proba, adds internal Platt folds on top.

Added probe_max_samples, defaulting to the authors' values, and probe_cases_
records what the probe was actually fitted on. The four timeouts are
rerunnable, and the missing_results rows say so rather than recording them as
a property of the method.

TS2Vec lands 20th of 26 on rank, mean accuracy 0.7212, which is above TimesURL,
the fork of it already in the archive.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
@TonyBagnall
TonyBagnall merged commit 815ad8e into main Sep 3, 2026
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