Demonstrating SubStrat: A Subset-Based Strategy for Faster AutoML on Large Datasets

Teddy Lazebnik, Amit Somech

نتاج البحث: فصل من :كتاب / تقرير / مؤتمرمنشور من مؤتمرمراجعة النظراء

1 اقتباس (Scopus)

ملخص

Automated machine learning (AutoML) frameworks are gaining popularity among data scientists as they dramatically reduce the manual work devoted to the construction of ML pipelines while obtaining similar and sometimes even better results than manually-built models. Such frameworks intelligently search among millions of possible ML pipeline configurations to finally retrieve an optimal pipeline in terms of predictive accuracy. However, when the training dataset is large, the construction and evaluation of a single ML pipeline take longer, which makes the overall AutoML running times increasingly high. To this end, in this work we demonstrate SubStrat, an AutoML optimization strategy that tackles the dataset size rather than the configurations search space. SubStrat wraps existing AutoML tools, and instead of executing them directly on the large dataset, it uses a genetic-based algorithm to find a small yet representative data subset that preserves characteristics of the original one. SubStrat then employs the AutoML tool on the generated subset, resulting in an intermediate ML pipeline, which is later refined by executing a restricted, much shorter, AutoML process on the large dataset. We demonstrate SubStrat on both AutoSklearn, TPOT, and H2O, three popular AutoML frameworks, using several real-life datasets.

اللغة الأصليةالإنجليزيّة
عنوان منشور المضيفCIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management
الصفحات4907-4911
عدد الصفحات5
رقم المعيار الدولي للكتب (الإلكتروني)9781450392365
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 17 أكتوبر 2022
منشور خارجيًانعم
الحدث31st ACM International Conference on Information and Knowledge Management, CIKM 2022 - Atlanta, الولايات المتّحدة
المدة: ١٧ أكتوبر ٢٠٢٢٢١ أكتوبر ٢٠٢٢

سلسلة المنشورات

الاسمInternational Conference on Information and Knowledge Management, Proceedings

!!Conference

!!Conference31st ACM International Conference on Information and Knowledge Management, CIKM 2022
الدولة/الإقليمالولايات المتّحدة
المدينةAtlanta
المدة١٧/١٠/٢٢٢١/١٠/٢٢

بصمة

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