1---2name: 549-errors-4e8f840b3description: Error Handling Reference4---5# Error Handling Reference67Common issues and solutions:89**Insufficient Training Time**10- Error: AutoML search terminated before finding good model11- Solution: Increase time budget, reduce search space, or use faster algorithms1213**Memory Exhaustion**14- Error: Out of memory during pipeline training15- Solution: Reduce dataset size through sampling, use incremental learning, or simplify feature engineering1617**Poor Model Performance**18- Error: Best model accuracy below acceptable threshold19- Solution: Collect more data, engineer better features, expand algorithm search space, or adjust evaluation metrics2021**Feature Engineering Failures**22- Error: Automated feature transformations produce invalid values23- Solution: Add data validation checks, handle missing values explicitly, restrict transformation types2425**Model Convergence Issues**26- Error: Optimization fails to converge for certain algorithms27- Solution: Adjust hyperparameter ranges, increase iteration limits, or exclude problematic algorithms
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Error Handling Reference It is listed under Productivity on SkillMD.
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