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Vectle found the following relevant skills: - PyOD detector failed error "ValueError: Input contains infinity or a value too large" - forecasting model failed error "input DataFrame must have exactly two columns: ds and y"
Vectle found the following relevant skills: - anomaly model failed error "sklearn.exceptions.NotFittedError: This IsolationForest instance is not fitted yet" - [anomaly model failed error "sklearn.exceptions.NotFittedError: This IsolationForest …
Vectle found the following relevant skills: - anomaly model failed error "sklearn.exceptions.NotFittedError: This IsolationForest instance is not fitted yet" - [anomaly model failed error "sklearn.exceptions.NotFittedError: This IsolationForest …
Vectle found the following relevant skills: - Kats detector failed error "detector model requires at least 30 data points" - forecasting model failed error "input DataFrame must have exactly two columns: ds and y"
Fixes the CTGAN failure Loss became NaN by applying the specific fix in the steps, proving it on one small scope first, then rerunning and reconciling counts. Use when this error blocks generation, validation or export. Not for platform outages, which must be resolved first.
Fixes the PyOD failure "ValueError: Input contains infinity or a value too large" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permission errors, which must be resolved first.
Vectle found the following relevant skills: - agent hallucinating threshold values error failed to use configured detector settings - Error: Invalid value for variable: input failed the variable validation block
Fixes the statsmodels failure "ValueError: endog must be strictly positive" by acting on the exact message, proving the fix on one item, then rerunning and reconciling counts. Use when this error blocks an export, review or check. Not for platform outages or permission errors, which must be resolved first.
Fail the run on NaN instead of recording it as healthy: the tracker logged NaN for every epoch while the run shows green, so add a metric sanity check that marks the run failed when the primary metric is NaN, and fix the training instability that produced it. Use when a tracked training workflow where run status comes…
Fixes the GaussianCopula failure singular matrix by applying the specific fix in the steps, proving it on one small scope first, then rerunning and reconciling counts. Use when this error blocks generation, validation or export. Not for platform outages, which must be resolved first.