Average RMSE rank for all combinations of subsampling scenarios and algorithms.

Average RMSE rank for all combinations of subsampling scenarios and algorithms.

<p>RMSE values were ranked for each drug and were then averaged. Lower ranks imply a better result. We also include standard deviation and the minimum and maximum RMSE values.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Sofia P. Miranda (11418930) (author)
مؤلفون آخرون:	Fernanda A. Baião (10451272) (author), Julia L. Fleck (9519670) (author), Stephen R. Piccolo (8367780) (author)
منشور في:	2021
الموضوعات:	Genetics Pharmacology Cancer Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified test sets consisted random forests algorithm dna methylation profiles human tumors based modulate treatment responses classifying clinical responses studied preclinical models relatively extreme drug cancer cells based predict cytotoxic responses cancer genome atlas cell cultures derived 987 cell lines predicting drug sensitivity five classification algorithms used patient data models derived cell lines drug sensitivity based approaches temozolomide responses continuous responses using genome using classification predict discrete cancer drugs cancer database models using optimize drug drug development varying degrees used machine tumor samples significantly correlated response values represent one regression algorithms one type molecular feature line data least expensive learning algorithms identify patterns full range eight anti drive tumorigenesis development pipelines curve values attaining area artificially subsampled
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